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Journal articles on the topic 'Nominal Response Model (NRM)'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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1

Zu, Jiyun, and Patrick C. Kyllonen. "Nominal Response Model Is Useful for Scoring Multiple-Choice Situational Judgment Tests." Organizational Research Methods 23, no. 2 (November 25, 2018): 342–66. http://dx.doi.org/10.1177/1094428118812669.

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We evaluated the use of the nominal response model (NRM) to score multiple-choice (also known as “select the best option”) situational judgment tests (SJTs). Using data from two large studies, we compared the reliability and correlations of NRM scores with those from various classical and item response theory (IRT) scoring methods. The SJTs measured emotional management (Study 1) and teamwork and collaboration (Study 2). In Study 1 the NRM scoring method was shown to be superior in reliability and in yielding higher correlations with external measures to three classical test theory–based and four other IRT-based methods. In Study 2, only slight differences between scoring methods were observed. An explanation for the discrepancy in findings is that in cases where item keys are ambiguous (as in Study 1), the NRM accommodates that ambiguity, but in cases where item keys are clear (as in Study 2), different methods provide interchangeable scores. We characterize ambiguous and clear keys using category response curves based on parameter estimates of the NRM and discuss the relationships between our findings and those from the wisdom-of-the-crowd literature.

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2

García-Pérez, Miguel A. "Order-Constrained Estimation of Nominal Response Model Parameters to Assess the Empirical Order of Categories." Educational and Psychological Measurement 78, no. 5 (June 19, 2017): 826–56. http://dx.doi.org/10.1177/0013164417714296.

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Bock’s nominal response model (NRM) is sometimes used to identify the empirical order of response categories in polytomous items but its application tags many items as having disordered categories. Disorderly estimated categories may not reflect a true characteristic of the items but, rather, a numerically best-fitting solution possibly equivalent to other solutions with orderly estimated categories. To investigate this possibility, an order-constrained variant of the NRM was developed that enforces the preassumed order of categories on parameter estimates, for a comparison of its outcomes with those of the original unconstrained NRM. For items with ordered categories, order-constrained and unconstrained solutions should account for the data equally well even if the latter solution estimated disordered categories for some items; for items with truly disordered categories, the unconstrained solution should outperform the order-constrained solution. Criteria for this comparative analysis are defined and their utility is tested in several simulation studies with items of diverse characteristics, including ordered and disordered categories. The results demonstrate that a comparison of order-constrained and unconstrained calibrations on such criteria provides the evidence needed to determine whether category disorder estimated on some items by the original unconstrained form of the NRM is authentic or spurious. Applications of this method to assess category order in existing data sets are presented and practical implications are discussed.

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Matlock, Ki Lynn, Ronna C. Turner, and W. Dent Gitchel. "A Study of Reverse-Worded Matched Item Pairs Using the Generalized Partial Credit and Nominal Response Models." Educational and Psychological Measurement 78, no. 1 (October 6, 2016): 103–27. http://dx.doi.org/10.1177/0013164416670211.

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The generalized partial credit model (GPCM) is often used for polytomous data; however, the nominal response model (NRM) allows for the investigation of how adjacent categories may discriminate differently when items are positively or negatively worded. Ten items from three different self-reported scales were used (anxiety, depression, and perceived stress), and authors wrote an additional item worded in the opposite direction to pair with each original item. Sets of the original and reverse-worded items were administered, and responses were analyzed using the two models. The NRM fit significantly better than the GPCM, and it was able to detect category responses that may not function well. Positively worded items tended to be more discriminating than negatively worded items. For the depression scale, category boundary locations tended to have a larger range for the positively worded items than for the negatively worded items from both models. Some pairs of items functioned comparably when reverse-worded, but others did not. If an examinee responds in an extreme category to an item, the same examinee is not necessarily likely to respond in an extreme category at the opposite end of the rating scale to a similar item worded in the opposite direction. Results of this study may support the use of scales composed of items worded in the same direction, and particularly in the positive direction.

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Harel, Daphna, and Russell J. Steele. "An Information Matrix Test for the Collapsing of Categories Under the Partial Credit Model." Journal of Educational and Behavioral Statistics 43, no. 6 (July 16, 2018): 721–50. http://dx.doi.org/10.3102/1076998618787478.

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Collapsing categories is a commonly used data reduction technique; however, to date there do not exist principled methods to determine whether collapsing categories is appropriate in practice. With ordinal responses under the partial credit model, when collapsing categories, the true model for the collapsed data is no longer a partial credit model, and therefore refitting a partial credit model may result in model misspecification. This article details the implementation and performance of an information matrix test (IMT) to assess the implications of collapsing categories for a given data set under the partial credit model and compares its performance to the application of a nominal response model (NRM) and the S − X2 goodness-of-fit statistic. The IMT and NRM-based test are able to correctly determine the true number of categories for an item, given reasonable power through this goodness-of-fit test. We conclude by applying the test to a well-studied data set from the literature.

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5

Jefmański, Bartłomiej, and Adam Sagan. "Item Response Theory Models for the Fuzzy TOPSIS in the Analysis of Survey Data." Symmetry 13, no. 2 (January 29, 2021): 223. http://dx.doi.org/10.3390/sym13020223.

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The fuzzy TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) is an attractive tool for measuring complex phenomena based on uncertain data. The original version of the method assumes that the object assessments in terms of the adopted criteria are expressed as triangular fuzzy numbers. One of the crucial stages of the fuzzy TOPSIS is selecting the fuzzy conversion scale, which is used to evaluate objects in terms of the adopted criteria. The choice of a fuzzy conversion scale may influence the results of the fuzzy TOPSIS. There is no uniform approach in constructing and selecting the fuzzy conversion scale for the fuzzy TOPSIS. The choice is subjective and made by researchers. Therefore, the aim of the article is to present a new, objective approach to the construction of fuzzy conversion scales based on Item Response Theory (IRT) models. The following models were used in the construction of fuzzy conversion scales: Polychoric Correlation Model (PM), Polytomous Rasch Model (PRM), Rating Scale Model (RSM), Partial Credit Model (PCM), Generalized Partial Credit Model (GPCM), Graded Response Model (GRM), Nominal Response Model (NRM). The usefulness of the proposed approach is presented on the example of the analysis of a survey’s results on measuring the quality of professional life of inhabitants of selected communes in Poland. The obtained results indicate that the choice of the fuzzy conversion scale has a large impact on the closeness coefficient values. A large difference was also observed in the spreads of triangular fuzzy numbers between scales based on IRT models and those used in the literature on the subject. The use of the fuzzy TOPSIS with fuzzy conversion scales built based on PRM, RSM, PCM, GPCM, and GRM models gives results with a greater range of variability than in the case of fuzzy conversion scales used in empirical research.

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6

Percival, Mary-Elizabeth M., Hai-Lin Wang, Mei-Jie Zhang, Elihu H. Estey, Mark Litzow, Partow Kebriaei, Marcos de Lima, Wael Saber, Daniel J. Weisdorf, and Brenda M. Sandmaier. "Impact of Depth of Pretransplant Clinical Response on Outcomes of Acute Myeloid Leukemia Patients in First Complete Remission (AML-CR1) Who Undergo Allogeneic Hematopoietic Cell Transplantation (AlloHCT)." Blood 134, Supplement_1 (November 13, 2019): 4585. http://dx.doi.org/10.1182/blood-2019-123510.

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Introduction: AML patients with intermediate or high-risk features often undergo allogeneic hematopoietic cell transplantation (alloHCT) during first complete remission (CR). The 2017 European LeukemiaNet guidelines for AML specify categories of CR: both with and without count recovery (CR vs. CRi) and with and without measurable residual disease (MRD). Previous smaller retrospective studies have suggested poorer survival outcomes after alloHCT for patients with responses less than CR. Methods: Eligible cases were determined using the CIBMTR registry. Each had AML in CR1, was ≥ 18 years, and underwent alloHCT between January 1, 2007 and December 31, 2015. MRD was defined based on the answers to qualitative questions on standard clinical reporting forms that ask if the patient is in either molecular or cytogenetic remission and if disease is detected in marrow by flow cytometry at time of HCT. The primary outcome was overall survival (OS), and secondary outcomes were non-relapse mortality (NRM), relapse and disease-free survival (DFS). The Kaplan-Meier method was used to estimate survival and cumulative incidence function was used to estimate relapse and NRM. Multivariable analysis (MVA) was performed using the Cox proportional hazards model to adjust for patient-, disease-, and transplant-related factors. Adjusted probabilities of DFS and OS, adjusted cumulative incidence curves of NRM and relapse were generated from final Cox regression models stratified on CR vs. CRi and weighted averages of covariate values using pooled sample proportion as weight function. Results: We identified 2492 cases (CR, n=1799; CRi, n=693). The main effect variable (CR vs. CRi) was missing in 262 additional patients; these patients were excluded when univariate analysis confirmed no significant associations, suggesting a random distribution of missing data. Patient characteristics are summarized in Table 1. Compared with patients with CR, patients with CRi were more likely to have a Karnofsky score <90 (38% vs. 31%) and an HCT-CI score 3+ (47% vs. 40%). Other variables were well matched between the groups. MVA demonstrated significantly increased likelihood of mortality in patients with CRi compared to those with CR with hazard ratio (HR) 1.27; 95% confidence interval (CI) (1.13-1.43) (Figure 1A). Other covariates significantly associated with shorter OS included older age, poor-risk cytogenetics, lower Karnofsky score, higher HCT-CI score, and higher white blood cell count at diagnosis. The adjusted OS probabilities at 5 year post-HCT accounted for factors from MVA model are 50% (95%CI 47-52) for patients with CR and 43% (95%CI 39-47) for patients with CRi. CRi was also associated with significantly increased NRM [HR 1.33, 95%CI(1.11-1.59)] with only a trend in increased relapse [HR 1.15, 95% CI(0.99-1.34), p=0.07] resulting in inferior DFS [HR 1.20, 95%CI(1.07-1.35)]. MRD status was available in a subset of 2297 patients, and pairwise comparison demonstrated that presence of MRD was associated with shorter OS, shorter DFS, higher NRM, and increased relapse compared to absence of MRD (Figure 1B). Pairwise interaction between the main effects (CR vs. CRi) and MRD status were tested with no significant findings at a level of 0.01, demonstrating that the effects of incomplete count recovery and MRD are independent of each other. Conclusions: Analysis of this large CIBMTR cohort demonstrates that survival outcomes differ among AML patients nominally in CR at the time of alloHCT. Patients with CRi and/or MRD have significantly shorter OS after alloHCT compared to those in CR, as well as shorter DFS and higher NRM. Further studies should focus on limiting NRM and reducing relapse to optimize post-alloHCT outcomes for patients with responses less than CR. Disclosures Percival: Pfizer Inc.: Research Funding; Nohla Therapeutics: Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees. Kebriaei:Jazz: Consultancy; Pfizer: Honoraria; Amgen: Research Funding; Kite: Honoraria. Weisdorf:Fate Therapeutics: Consultancy; Incyte: Research Funding; Pharmacyclics: Consultancy.

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7

Storme, Martin, Nils Myszkowski, Simon Baron, and David Bernard. "Same Test, Better Scores: Boosting the Reliability of Short Online Intelligence Recruitment Tests with Nested Logit Item Response Theory Models." Journal of Intelligence 7, no. 3 (July 10, 2019): 17. http://dx.doi.org/10.3390/jintelligence7030017.

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Assessing job applicants’ general mental ability online poses psychometric challenges due to the necessity of having brief but accurate tests. Recent research (Myszkowski & Storme, 2018) suggests that recovering distractor information through Nested Logit Models (NLM; Suh & Bolt, 2010) increases the reliability of ability estimates in reasoning matrix-type tests. In the present research, we extended this result to a different context (online intelligence testing for recruitment) and in a larger sample ( N = 2949 job applicants). We found that the NLMs outperformed the Nominal Response Model (Bock, 1970) and provided significant reliability gains compared with their binary logistic counterparts. In line with previous research, the gain in reliability was especially obtained at low ability levels. Implications and practical recommendations are discussed.

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8

Battauz, Michela. "Regularized Estimation of the Nominal Response Model." Multivariate Behavioral Research 55, no. 6 (November 4, 2019): 811–24. http://dx.doi.org/10.1080/00273171.2019.1681252.

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9

Revuelta, Javier. "Multidimensional Item Response Model for Nominal Variables." Applied Psychological Measurement 38, no. 7 (June 17, 2014): 549–62. http://dx.doi.org/10.1177/0146621614536272.

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10

Baker, Frank B. "Equating Tests Under The Nominal Response Model." Applied Psychological Measurement 17, no. 3 (September 1993): 239–51. http://dx.doi.org/10.1177/014662169301700305.

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11

Preston, Kathleen Suzanne Johnson, and Steven Paul Reise. "Estimating the Nominal Response Model Under Nonnormal Conditions." Educational and Psychological Measurement 74, no. 3 (October 25, 2013): 377–99. http://dx.doi.org/10.1177/0013164413507063.

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12

De Ayala, R. J. "The Nominal Response Model in Computerized Adaptive Testing." Applied Psychological Measurement 16, no. 4 (December 1992): 327–43. http://dx.doi.org/10.1177/014662169201600403.

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13

De Ayala, R. J., and Monica Sava-Bolesta. "Item Parameter Recovery for the Nominal Response Model." Applied Psychological Measurement 23, no. 1 (March 1999): 3–19. http://dx.doi.org/10.1177/01466219922031130.

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14

Kim, Seonghoon. "Linking Ability Scales Under the Multidimensional Nominal Response Model." Korean Society for Educational Evaluation 33, no. 3 (September 30, 2020): 655–79. http://dx.doi.org/10.31158/jeev.2020.33.3.655.

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15

Wollack, James A. "A Nominal Response Model Approach for Detecting Answer Copying." Applied Psychological Measurement 21, no. 4 (December 1997): 307–20. http://dx.doi.org/10.1177/01466216970214002.

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16

Leventhal, Brian C. "Extreme Response Style: A Simulation Study Comparison of Three Multidimensional Item Response Models." Applied Psychological Measurement 43, no. 4 (August 1, 2018): 322–35. http://dx.doi.org/10.1177/0146621618789392.

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Several multidimensional item response models have been proposed for survey responses affected by response styles. Through simulation, this study compares three models designed to account for extreme response tendencies: the IRTree Model, the multidimensional nominal response model, and the modified generalized partial credit model. The modified generalized partial credit model results in the lowest item mean squared error (MSE) across simulation conditions of sample size (500, 1,000), survey length (10, 20), and number of response options (4, 6). The multidimensional nominal response model is equally suitable for surveys measuring one substantive trait using responses to 10 four-option, forced-choice Likert-type items. Based on data validation, comparison of item MSE, and posterior predictive model checking, the IRTree Model is hypothesized to account for additional sources of construct-irrelevant variance.

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17

Evans, Sarah, Katherine E. O. Todd-Brown, Kathryn Jacobson, and Peter Jacobson. "Non-rainfall Moisture: A Key Driver of Microbial Respiration from Standing Litter in Arid, Semiarid, and Mesic Grasslands." Ecosystems 23, no. 6 (December 2, 2019): 1154–69. http://dx.doi.org/10.1007/s10021-019-00461-y.

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Abstract Models assume that rainfall is the major moisture source driving decomposition. Non-rainfall moisture (NRM: high humidity, dew, and fog) can also induce standing litter decomposition, but there have been few measurements of NRM-mediated decomposition across sites and no efforts to extrapolate the contribution of NRM to larger scales to assess whether this mechanism can improve model predictions. Here, we show that NRM is an important, year-round source of moisture in grassland sites with contrasting moisture regimes using field measurements and modeling. We first characterized NRM frequency and measured NRM-mediated decomposition at two sites in the Namib Desert, Namibia (hyper-arid desert), and at one site in Iowa, USA (tallgrass prairie). NRM was frequent at all sites (85–99% of hours that litter was likely to be wet were attributed to NRM) and tended to occur in cool, high-humidity periods for several hours or more at a time. NRM also resulted in CO2 release from microbes in standing litter at all sites when litter became sufficiently wet (> 5% gravimetric moisture for fine litter and > 13% for coarse), and significantly contributed to mass loss, particularly in the western Namib site that received almost no rain. When we modeled annual mass loss induced by NRM and rain and extrapolated our characterization of NRM decomposition to a final semiarid site (Sevilleta, New Mexico), we found that models driven by rainfall alone underestimated mass loss, while including NRM resulted in estimates within the range of observed mass loss. Together these findings suggest that NRM is an important missing component in quantitative and conceptual models of litter decomposition, but there is nuance involved in modeling NRM at larger scales. Specifically, temperature and physical features of the substrate emerge as factors that affect the microbial response to litter wetting under NRM in our sites, and require further study. Hourly humidity can provide an adequate proxy of NRM frequency, but site-specific calibration with litter wetness is needed to accurately attribute decomposition to periods when NRM wets litter. Greater recognition of NRM-driven decomposition and its interaction with other processes like photodegradation is needed, especially since fog, dew, and humidity are likely to shift under future climates.

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Kim, Seonghoon. "Reparameterization for Bock’s Nominal Response Model: Original Version Versus New Version." Korean Society for Educational Evaluation 32, no. 3 (September 30, 2019): 397–420. http://dx.doi.org/10.31158/jeev.2019.32.3.397.

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19

DeMars, Christine E. "Sample Size and the Recovery of Nominal Response Model Item Parameters." Applied Psychological Measurement 27, no. 4 (July 2003): 275–88. http://dx.doi.org/10.1177/0146621603027004003.

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20

Passos, Valeria Lima, and Martijn P. F. Berger. "Maximin Calibration Designs for the Nominal Response Model: an Empirical Evaluation." Applied Psychological Measurement 28, no. 1 (January 2004): 72–87. http://dx.doi.org/10.1177/0146621603260676.

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21

Glas, Cees A. W. "Modification indices for the 2-PL and the nominal response model." Psychometrika 64, no. 3 (September 1999): 273–94. http://dx.doi.org/10.1007/bf02294296.

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22

Lima Passos, Valeria, Martijn P. F. Berger, and Frans E. Tan. "Test Design Optimization in CAT Early Stage with the Nominal Response Model." Applied Psychological Measurement 31, no. 3 (May 2007): 213–32. http://dx.doi.org/10.1177/0146621606291571.

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23

Iacoviello, Matteo. "House Prices, Borrowing Constraints, and Monetary Policy in the Business Cycle." American Economic Review 95, no. 3 (May 1, 2005): 739–64. http://dx.doi.org/10.1257/0002828054201477.

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I develop and estimate a monetary business cycle model with nominal loans and collateral constraints tied to housing values. Demand shocks move housing and nominal prices in the same direction, and are amplified and propagated over time. The financial accelerator is not uniform: nominal debt dampens supply shocks, stabilizing the economy under interest rate control. Structural estimation supports two key model features: collateral effects dramatically improve the response of aggregate demand to housing price shocks; and nominal debt improves the sluggish response of output to inflation surprises. Finally, policy evaluation considers the role of house prices and debt indexation in affecting monetary policy trade-offs.

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van der Linden, Wim J., and Leonardo Sotaridona. "Detecting Answer Copying When the Regular Response Process Follows a Known Response Model." Journal of Educational and Behavioral Statistics 31, no. 3 (September 2006): 283–304. http://dx.doi.org/10.3102/10769986031003283.

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A statistical test for detecting answer copying on multiple-choice items is presented. The test is based on the exact null distribution of the number of random matches between two test takers under the assumption that the response process follows a known response model. The null distribution can easily be generalized to the family of distributions of the number of random matches under the alternative hypothesis of answer copying. It is shown how this information can be used to calculate such features as the maximum, minimum, and expected values of the power function of the test. For the case of the nominal response model, the test is an alternative to the one based on statistic ω. The differences between the two tests are discussed and illustrated using empirical results.

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Harris, Andrew C., James L. M. Ferrara, Joel K. Greenson, Thomas M. Braun, Ernst Holler, Takanori Teshima, John E. Levine, et al. "A Novel Grading System of Lower Gastrointestinal Acute Graft-Versus-Host Disease At Disease Onset Predicts Response to Therapy and Non-Relapse Mortality." Blood 118, no. 21 (November 18, 2011): 153. http://dx.doi.org/10.1182/blood.v118.21.153.153.

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Abstract Abstract 153 We have recently described REG3α as a plasma biomarker of lower gastrointestinal (GI) graft-versus-host disease (GVHD), the target GVHD organ most associated with increased non-relapse mortality (NRM) following hematopoietic cell transplantation (HCT), that provides important diagnostic and prognostic information in 1014 HCT patients from 3 transplant centers (BBMT; 17: S163–164). Histologic and clinical severity of lower GI GVHD have not consistently correlated with transplant outcomes and thus there is no established system for risk stratification for patients at the onset of lower GI GVHD when stratification would be most beneficial. We hypothesized that incorporation of characteristics evaluable at the onset GVHD such as plasma REG3α and albumin concentrations and clinical and histologic severity could help identify patients at the time of GVHD diagnosis who are unlikely to respond to conventional therapy and thus are at greatest risk of NRM. Plasma REG3α concentrations, serum albumin concentrations, clinical stage, and histologic grade as defined by Lerner (Transplant Proc; 6: 367–71) were all available at GVHD diagnosis for 140 patients experiencing lower GI GVHD from 3 HCT centers (129 from the University of Michigan and 11 from Regensburg, Germany, and Kyushu, Japan). Patients with lower GI GVHD who did not respond to GVHD therapy at 4 weeks had REG3α concentrations over 3-fold higher at onset than those who experienced at least a partial response (p<0.001). Patients with lower GI GVHD who had onset plasma REG3α concentrations above the median (>151 ng/ml) had increased 1-year NRM compared to those who had concentrations below the median (≤151 ng/ml; 59% versus 34%, respectively; p<0.001; Figure 1A). NRM was modeled with cumulative incidence regression methods as described by Fine and Gray (J Am Stat Assoc; 94: 496–509); probability of response was modeled with logistic regression. We performed an independent model analysis and found all 4 risk factors independently predicted lack of response to GVHD therapy four weeks following treatment and predicted 1-year NRM after adjustment for known risk factors of donor type, degree of HLA match, conditioning intensity, age and baseline disease severity (odds ratios: 4.8, 3.9, 18.9, and 2.5, respectively; Table 1). When lack of response to therapy and NRM were modeled simultaneously on all four parameters, all but albumin remained statistically significant when adjusting for the aforementioned risk factors. High REG3α concentration and histologic grade displayed the highest odds ratios for no response to treatment (5.7 and 16.7, respectively), while advanced clinical stage and histologic grade provided the highest hazard ratio for NRM (3.1 and 2.9, respectively). When only advanced clinical stage and severe histologic grade were considered, NRM was 71% (Figure 1B), but the inclusion of high REG3α concentration produced a significantly greater NRM of 86% for patients with all three risk factors (p<0.001; Figure 1C). Patients with increasing numbers of high risk parameters had increasing rates of NRM. Thus all three high risk parameters provided important prognostic information prior to the initiation of therapy rather than at the time of maximum grade of GVHD. If the prognostic value of REG3α is confirmed in additional patients, we believe the integration of clinical stage, histologic grade and REG3α plasma concentrations into a single grading system will permit better risk stratification and rapid identification of those patients with severe GI damage in whom standard treatment is likely to be insufficient.Table 1.REG3α concentrations and characteristics at onset of GVHD diarrhea predict 4-week response to GVHD therapy and 1-year NRM.No response to treatment (at 4 weeks)IndependentSimultaneousOdds Ratiop-value*Odds Ratiop-value*REG3α (high vs. low)4.8<0.0015.70.001GVHD GI onset stage (2–4 vs. 1)3.90.0013.00.027Histologic grade (4 vs. 1–3)18.9<0.00116.7<0.001Albumin (low vs. high)2.50.021.40.5IndependentSimultaneous1-Year NRMHazard Ratiop-value*Hazard Ratiop-value*REG3α (high vs. low)2.20.0032.40.002GVHD GI onset stage (2–4 vs. 1)3.0<0.0013.1<0.001Histologic grade (4 vs. 1–3)3.6<0.0012.9<0.001Albumin (low vs. high)2.30.0041.60.2*Adjusted for age, donor type, HLA match, conditioning intensity and disease status at transplant. Disclosures: No relevant conflicts of interest to declare.

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Azevedo, Caio L. N., and Dalton F. Andrade. "An estimation method for latent traits and population parameters in Nominal Response Model." Brazilian Journal of Probability and Statistics 24, no. 3 (November 2010): 415–33. http://dx.doi.org/10.1214/09-bjps102.

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27

Ju, Unhee, and Carl F. Falk. "Modeling Response Styles in Cross‐Country Self‐Reports: An Application of a Multilevel Multidimensional Nominal Response Model." Journal of Educational Measurement 56, no. 1 (March 2019): 169–91. http://dx.doi.org/10.1111/jedm.12205.

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28

Preston, Kathleen, Steven Reise, Li Cai, and Ron D. Hays. "Using the Nominal Response Model to Evaluate Response Category Discrimination in the PROMIS Emotional Distress Item Pools." Educational and Psychological Measurement 71, no. 3 (May 2, 2011): 523–50. http://dx.doi.org/10.1177/0013164410382250.

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29

Chen, Bor-Sen, and Tsang-Yi Yang. "Robust Optimal Model Matching Control Design for Flexible Manipulators." Journal of Dynamic Systems, Measurement, and Control 115, no. 1 (March 1, 1993): 173–78. http://dx.doi.org/10.1115/1.2897393.

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In this paper, the two-parameter compensator technique is used to control the one-link flexible robot arm theoretically. The rigid-body mode and the first flexible mode are considered as the nominal model and the other flexible modes are considered as unmodeled dynamics. The sufficient condition for stabilizing the nominal model against the unmodeled flexible dynamics is derived. The first control parameter is employed to robustly stabilize the one-link flexible robot arm against the unmodeled dynamics and the second one is specified to make the response of the system follow the desired reference model. Simulation results are included to demonstrate the performance of the compensator.

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De Ayala, R. J. "A Comparison of the Nominal Response Model and the Three-Parameter Logistic Model in Computerized Adaptive Testing." Educational and Psychological Measurement 49, no. 4 (December 1989): 789–805. http://dx.doi.org/10.1177/001316448904900403.

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Revuelta, Javier. "An Item Response Model for Nominal Data Based on the Rising Selection Ratios Criterion." Psychometrika 70, no. 2 (May 19, 2005): 305–24. http://dx.doi.org/10.1007/s11336-002-0975-y.

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32

Streit, D. A., C. M. Krousgrill, and A. K. Bajaj. "Nonlinear Response of Flexible Robotic Manipulators Performing Repetitive Tasks." Journal of Dynamic Systems, Measurement, and Control 111, no. 3 (September 1, 1989): 470–79. http://dx.doi.org/10.1115/1.3153077.

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The dynamics of a flexible manipulator is described by two distinct types of variables, one describing the nominal motion and the other describing the compliant motion. For a manipulator programmed to perform repetitive tasks, the dynamical equations governing the compliant motion are parametrically excited. Nonlinear dynamics of a two-degree-of-freedom model is investigated in parameter regions where the nominal motion is predicted by the Floquet theory to be unstable. Multiple time scales technique is used to study the nonlinear response, and it is shown that the compliant coordinates can execute small but finite amplitude periodic motions. In one particular case, the amplitude of these periodic motions is shown to bifurcate to a periodic solution which subsequently undergoes period-doubling bifurcations leading to chaotic motions.

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Bolt, Daniel M., Allan S. Cohen, and James A. Wollack. "A Mixture Item Response Model for Multiple-Choice Data." Journal of Educational and Behavioral Statistics 26, no. 4 (December 2001): 381–409. http://dx.doi.org/10.3102/10769986026004381.

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A mixture item response model is proposed for investigating individual differences in the selection of response categories in multiple-choice items. The model accounts for local dependence among response categories by assuming that examinees belong to discrete latent classes that have different propensities towards those responses. Varying response category propensities are captured by allowing the category intercept parameters in a nominal response model ( Bock, 1972 ) to assume different values across classes. A Markov Chain Monte Carlo algorithm for the estimation of model parameters and classification of examinees is described. A real-data example illustrates how the model can be used to distinguish examinees that are disproportionately attracted to different types of distractors in a test of English usage. A simulation study evaluates item parameter recovery and classification accuracy in a hypothetical multiple-choice test designed to be diagnostic. Implications for test construction and the use of multiple-choice tests to perform cognitive diagnoses of item response patterns are discussed.

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Levine, John E., Thomas M. Braun, Andrew C. Harris, Ernst Holler, Austin Taylor, Holly K. Miller, John M. Magenau, et al. "A Biomarker Algorithm Defines Onset Grades of Acute Graft-Vs-Host Disease with Distinct Non-Relapse Mortality." Blood 124, no. 21 (December 6, 2014): 661. http://dx.doi.org/10.1182/blood.v124.21.661.661.

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Abstract The severity of symptoms at the onset of graft versus host disease (GVHD) does not accurately define risk, and thus most patients (pts) are treated alike with high dose systemic steroids. We hypothesized that concentrations of one or more plasma biomarkers at the time of GVHD diagnosis could define distinct non-relapse mortality (NRM) risk grades that could guide treatment in a multicenter setting. We first analyzed plasma that was prospectively collected at acute GVHD onset from 492 HCT pts from 2 centers, which we randomly divided into training (n=328) and validation (n=164) sets; 300 HCT pts who enrolled on multicenter BMT CTN primary GVHD therapy clinical trials provided a second validation set. We measured the concentrations of 3 prognostic biomarkers (TNFR1, REG3α, and ST2) and used competing risks regression to create an algorithm from the training set to compute a predicted probability (p) of 6 mo NRM from GVHD diagnosis where log[-log(1-p)] = -9.169 + 0.598(log2TNFR1) - 0.028(log2REG3α) + 0.189(log2ST2). We then rank ordered p from lowest to highest and identified thresholds that met predetermined criteria for 3 GVHD grades so that NRM would increase 15% on average with each grade. A range of thresholds in the training set met these criteria, and we chose one near each median to demarcate each grade. In the resulting grades, risk of NRM significantly increased with each grade after the onset of GVHD in both the training and validation sets (FIG 1A,B). Most (80%) NRM was due to steroid-refractory GI GVHD, even though surprisingly only half of these pts presented with GI symptoms. We next applied the biomarker algorithm and thresholds to the second multicenter validation set (n=300) and observed similarly significant differences in NRM (FIG 1C). Relapse, which was treated as a competing risk for NRM, did not differ among the three GVHD grades (Figure 1D-F). The differences in NRM thus translated into significantly different overall survival for each GVHD grade (Figure 1G-I). These differences in survival are explained by primary therapy response at day 28, which was highly statistically different for each of Ann Arbor grade (grade 1, 81%; grade 2, 68%; grade 3, 46%; p<0.001 for all comparisons). We performed additional analyses on the multicenter validation set of pts that developed GVHD after treatment with a wide spectrum of supportive care, conditioning and GVHD prophylaxis practices. As expected, the Glucksberg grade at GVHD onset did not correlate with NRM (data not shown). Despite small sample sizes, the same biomarker algorithm and thresholds defined three distinct risk strata for NRM within each Glucksberg grade (FIG 2A-C). Pts with the higher Ann Arbor grades were usually less likely to respond to treatment. Unexpectedly, approximately the same proportion of pts were assigned to each Ann Arbor grade (~25% grade 1, ~55% grade 2, ~20% grade 3) regardless of the Glucksberg grade (FIG 2D-F). Several clinical risk factors, such as donor type, age, conditioning, and HLA-match, can predict treatment response and survival in patients with GVHD. Using Ann Arbor grade 2 as a reference, we found that Ann Arbor grade 1 predicted a lower risk of NRM (range 0.16-0.32) and grade 3 a higher risk of NRM (range 1.4-2.9), whether or not any of these clinical risk factors were present. To directly compare Ann Arbor grades to Glucksberg grades, we fit a multivariate model with simultaneous adjustment for both grades. FIG 3 shows that Ann Arbor grade 3 pts had significantly higher risk for NRM (p=0.005) and Ann Arbor grade 1 pts had significantly less risk for NRM (p=0.002) than pts with Ann Arbor grade 2. By contrast, the confidence intervals for the HRs of the Glucksberg grades encompassed 1.0, demonstrating a lack of statistical significance between grades. In conclusion, we have developed and validated an algorithm of plasma biomarkers that define three grades of GVHD with distinct risks of NRM and treatment failure despite differences in clinical severity at presentation. The biomarkers at GVHD onset appear to reflect GI tract disease activity that does not correlate with GI symptom severity at the time. This algorithm may be useful in clinical trial design. For example, it can exclude pts who are likely to respond to standard therapy despite severe clinical presentations, thus limiting the exposure of low risk pts to investigational agents while also identifying the high risk pts most likely to benefit from investigational approaches. Figure 1 Figure 1. Figure 2 Figure 2. Figure 3 Figure 3. Disclosures Levine: University of Michigan: GVHD biomarker patent Patents & Royalties. Braun:University of Michigan: GVHD biomarker patent Patents & Royalties. Ferrara:University of Michigan: GVHD biomarker patent Patents & Royalties.

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Campos, Ana Carolina P., Miriã B. Berzuíno, Gabriela R. Barbosa, Helena M. R. C. Freire, Patricia S. Lopes, Danielle V. Assis, Erich T. Fonoff, and Rosana L. Pagano. "Motor Cortex Stimulation Reversed Hypernociception, Increased Serotonin in Raphe Neurons, and Caused Inhibition of Spinal Astrocytes in a Parkinson’s Disease Rat Model." Cells 10, no. 5 (May 11, 2021): 1158. http://dx.doi.org/10.3390/cells10051158.

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Persistent pain is a prevalent symptom of Parkinson’s disease (PD), which is related to the loss of monoamines and neuroinflammation. Motor cortex stimulation (MCS) inhibits persistent pain by activating the descending analgesic pathways; however, its effectiveness in the control of PD-induced pain remains unclear. Here, we evaluated the analgesic efficacy of MCS together with serotonergic and spinal glial modulation in an experimental PD (ePD) rat model. Wistar rats with unilateral striatal 6-OHDA and MCS were assessed for behavioral immobility and nociceptive responses. The immunoreactivity of dopamine in the substantia nigra and serotonin in the nucleus raphe magnus (NRM) and the neuronal, astrocytic, and microglial activation in the dorsal horn of the spinal cord were evaluated. MCS, without interfering with dopamine loss, reversed ePD-induced immobility and hypernociception. This response was accompanied by an exacerbated increase in serotonin in the NRM and a decrease in neuronal and astrocytic hyperactivation in the spinal cord, without inhibiting ePD-induced microglial hypertrophy and hyperplasia. Taken together, MCS induces analgesia in the ePD model, while restores the descending serotonergic pathway with consequent inhibition of spinal neurons and astrocytes, showing the role of MCS in PD-induced pain control.

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Srinagesh, Hrishikesh Krishna, Hrishikesh Krishna Srinagesh, Urvi Kapoor, Mina Aziz, Kaitlyn Ben-David, Hannah Major-Monfried, George Morales, et al. "3424 Serial Biomarker Monitoring Predicts Long Term Outcomes in Acute Graft Versus Host Disease." Journal of Clinical and Translational Science 3, s1 (March 2019): 114. http://dx.doi.org/10.1017/cts.2019.261.

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OBJECTIVES/SPECIFIC AIMS: The first aim of the study is to evaluate the accuracy of serum biomarkers of acute GVHD measured after four weeks of corticosteroid therapy to predict 6 month NRM. The second aim of this study is to compare the accuracy of the biomarker algorithm to that of clinical response to corticosteroids after four weeks. The third aim of the study is to develop a novel regression model that uses weekly biomarker measurements over the first month of corticosteroid therapy to predict 6 month NRM. METHODS/STUDY POPULATION:. Patients who received HCT at one of 22 IRB-approved centers and provided blood samples to the Mount Sinai Acute GVHD International Consortium (MAGIC) biorepository and developed GVHD between January 2008 to May 2018 are included in this study. Patients were divided by time into a training set (Jan 2008-Dec 2015, n=233) for model development and a validation set (Jan 2015-May 2018, n=357) to evaluate the predictive performance of the model. The later time of the validation set was chosen deliberately to model contemporaneous GVHD treatment practices. The size of each group was designed so that there would be roughly equal numbers of deaths in both groups. RESULTS/ANTICIPATED RESULTS:. Serum concentrations of GVHD biomarkers after one month of corticosteroid therapy were measured in the validation set, and the predicted probability of NRM ($\hat{\rm p}$) was computed according to the previously published algorithm: $\log[-\log(1 - \hat{\rm p})]=-11.263 + 1.844({\rm logST}2)+ 0.577({\rm logREG}3\alpha)$. The performance of the biomarker algorithm was evaluated by creating receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC) in the validation set. The AUC of the biomarker algorithm was a significantly better predictor of 6 month NRM than clinical response to treatment after four weeks of corticosteroids (0.84 vs. 0.64, p<0.001), which is a clinically relevant improvement in accuracy. To evaluate serial biomarker monitoring, serum biomarker concentrations will be measured weekly at five time points from treatment initiation to one month after corticosteroid therapy. We will use these values in the training set to develop a regression model for 6 month NRM that accounts for repeated biomarker measurements. The performance of this model will be tested in the validation set and the accuracy of the serial biomarker measurements will be compared to the accuracy of measuring biomarkers at the single time point after four weeks of corticosteroid therapy. An AUC improvement of 0.05 would be considered clinically significant. DISCUSSION/SIGNIFICANCE OF IMPACT: Clinical response to treatment after four weeks has been the standard endpoint in GVHD interventional trials for decades. If biomarkers measured at the same time more accurately predict long term mortality, this study would provide the basis for a novel endpoint in GVHD trials and enable more accurate determination of effect size of experimental interventions. An accurate biomarker algorithm will prove useful in guiding immunosuppressive treatment decisions for patients with GVHD. Patients identified by the algorithm as low-risk may benefit from reduced-dose corticosteroid therapy, potentially reducing lethal opportunistic infections. Patients identified as high-risk will be candidates for more intensive immunosuppression or investigational therapies. This precision medicine approach tailors therapy to the individual patient’s biology.

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Luo, Yong, and Hong Jiao. "Using the Stan Program for Bayesian Item Response Theory." Educational and Psychological Measurement 78, no. 3 (February 1, 2017): 384–408. http://dx.doi.org/10.1177/0013164417693666.

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Stan is a new Bayesian statistical software program that implements the powerful and efficient Hamiltonian Monte Carlo (HMC) algorithm. To date there is not a source that systematically provides Stan code for various item response theory (IRT) models. This article provides Stan code for three representative IRT models, including the three-parameter logistic IRT model, the graded response model, and the nominal response model. We demonstrate how IRT model comparison can be conducted with Stan and how the provided Stan code for simple IRT models can be easily extended to their multidimensional and multilevel cases.

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Bayrak, Abdurrahman, Handan Gürsoy, and Mehmet Önder Efe. "A novel robust fuzzy control of an uncertain system." Transactions of the Institute of Measurement and Control 39, no. 3 (October 7, 2016): 324–33. http://dx.doi.org/10.1177/0142331216668394.

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This paper presents a robust control method combining the conventional proportional–integral–derivative (PID) scheme and the sliding mode fuzzy control scheme for a second-order non-linear system having uncertainties in the system dynamics. The goal of the proposed scheme is to force the response of the uncertain plant to follow that of the nominal model. The first phase of the design approach is to obtain a nominal PID controller for the nominal plant model. The poor performance of the sole PID scheme on the uncertain non-linear system motivates the proposal of the technique discussed here. To compensate for the deficiencies in the unit step response of the uncertain system, a fuzzy compensation scheme based on sliding mode control (SMC) is proposed and the PID loop is augmented by the proposed approach. It is shown that the performance with the proposed scheme is better than the sole PID-based control system. With the proposed technique, the response of the uncertain system converges to of the nominal system with admissible controller outputs. Furthermore, simulation results show that the proposed method produces consistent results even with noisy measurements.

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Huggins-Manley, Anne Corinne, and James Algina. "The Partial Credit Model and Generalized Partial Credit Model as Constrained Nominal Response Models, With Applications in Mplus." Structural Equation Modeling: A Multidisciplinary Journal 22, no. 2 (January 6, 2015): 308–18. http://dx.doi.org/10.1080/10705511.2014.937374.

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Penfield, Randall D. "An Odds Ratio Approach for Assessing Differential Distractor Functioning Effects under the Nominal Response Model." Journal of Educational Measurement 45, no. 3 (September 2008): 247–69. http://dx.doi.org/10.1111/j.1745-3984.2008.00063.x.

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Quan, Nguyen Minh, Pham Minh Hai, and Dinh Van Phong. "The dynamic response of a rotor supported by two foil-air bearings with an enhanced model of foil structure." International Journal of Modern Physics B 34, no. 22n24 (August 26, 2020): 2040160. http://dx.doi.org/10.1142/s0217979220401608.

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Foil-air bearings have presented their advantageous performance due to their different structures when compared to traditional air bearings. However, it is the nonlinear characteristic of this kind of bearing that has drawn studies on dynamic response of the rotor-bearing system, especially rotor stability. In this paper, an improved foil dynamic model with internal bending moment included has been proposed to determine the nominal stiffness of the foil structure. Based on that, the nominal stiffness of the foil structure has been investigated with different geometry parameters of the foil structure. By such means, the stability of the rotor-bearings system has been theoretically studied through an equation system in a common turbocharger structure. The results can be effectively used for designing and suitably selecting some geometry parameters of foil-air bearings to have a good rotor performance in this case.

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Linnemann, Ludger, and Andreas Schabert. "Monetary Policy, Agency Costs and Output Dynamics." German Economic Review 4, no. 3 (August 1, 2003): 341–64. http://dx.doi.org/10.1111/1468-0475.00084.

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Abstract This paper examines the role of financial market imperfections for output reactions to nominal interest rate shocks. Empirical evidence shows a humpshaped impulse response function of output and suggests that credit supply co-moves with output. A monetary business cycle model with staggered price setting is presented where the firms’ outlays for capital and labor must be covered by the sum of net worth of entrepreneurs and loans in the form of debt contracts. These properties are shown to generate a hump-shaped impulse response of output, which takes on the smooth and persistent appearance of the empirical output response when nominal wages are set in a staggered way, too.

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Preston, Kathleen Suzanne Johnson, Skye N. Parral, Allen W. Gottfried, Pamella H. Oliver, Adele Eskeles Gottfried, Sirena M. Ibrahim, and Danielle Delany. "Applying the Nominal Response Model Within a Longitudinal Framework to Construct the Positive Family Relationships Scale." Educational and Psychological Measurement 75, no. 6 (January 26, 2015): 901–30. http://dx.doi.org/10.1177/0013164414568717.

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Wason, James MS, and Shaun R. Seaman. "A latent variable model for improving inference in trials assessing the effect of dose on toxicity and composite efficacy endpoints." Statistical Methods in Medical Research 29, no. 1 (February 25, 2019): 230–42. http://dx.doi.org/10.1177/0962280219831038.

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It is often of interest to explore how dose affects the toxicity and efficacy properties of a novel treatment. In oncology, efficacy is often assessed through response, which is defined by a patient having no new tumour lesions and their tumour size shrinking by 30%. Usually response and toxicity are analysed as binary outcomes in early phase trials. Methods have been proposed to improve the efficiency of analysing response by utilising the continuous tumour size information instead of dichotomising it. However, these methods do not allow for toxicity or for different doses. Motivated by a phase II trial testing multiple doses of a treatment against placebo, we propose a latent variable model that can estimate the probability of response and no toxicity (or other related outcomes) for different doses. We assess the confidence interval coverage and efficiency properties of the method, compared to methods that do not use the continuous tumour size, in a simulation study and the real study. The coverage is close to nominal when model assumptions are met, although can be below nominal when the model is misspecified. Compared to methods that treat response as binary, the method has confidence intervals with 30–50% narrower widths. The method adds considerable efficiency but care must be taken that the model assumptions are reasonable.

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Chen, Jinsong. "Advancing the Bayesian Approach for Multidimensional Polytomous and Nominal IRT Models." Applied Psychological Measurement 41, no. 1 (September 24, 2016): 3–16. http://dx.doi.org/10.1177/0146621616669096.

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It is common to encounter polytomous and nominal responses with latent variables in social or behavior research, and a variety of polytomous and nominal item response theory (IRT) models are available for applied researchers across diverse settings. With its flexibility and scalability, the Bayesian approach using the Markov chain Monte Carlo (MCMC) method demonstrates its great advantages for polytomous and nominal IRT models. However, the potential of the Bayesian approach would not be fully realized without model formulations that can cover various models and effective fit measures for model assessment or criticism. This research first provided formulations for typical models that are representative of different modeling groups. Then, a series of discrepancy measures that can offer diagnostic information for model-data misfit were introduced. Simulation studies showed that the formulation worked as expected, and some of the fit measures were more useful than the others or across different situations.

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Hyun, Seung Won, Weng Kee Wong, and Yarong Yang. "Optimal designs for asymmetric sigmoidal response curves in bioassays and immunoassays." Statistical Methods in Medical Research 29, no. 2 (March 14, 2019): 421–36. http://dx.doi.org/10.1177/0962280219832631.

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The 5-parameter logistic (5PL) model is frequently used to model and analyze responses from bioassays and immunoassays which can be skewed. Various types of optimal experimental designs for 2, 3 and 4-parameter logistic models have been reported but not for the more complicated 5PL model. We construct different types of optimal designs for studying various features of the 5PL model and show that commonly used designs in bioassays and immunoassays are generally inefficient for statistical inference. To facilitate use of such designs in practice, we create a user-friendly software package to generate various tailor-made optimal designs for the 5PL model and evaluate robustness properties of a design under a variation of criteria, model forms and misspecification in the nominal values of the model parameters.

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Moulton, Sara E., Ellie L. Young, and Richard R. Sudweeks. "Examining the Psychometric Properties of the SRSS-IE With the Nominal Response Model Within a Middle School Sample." Assessment for Effective Intervention 44, no. 4 (May 30, 2018): 227–40. http://dx.doi.org/10.1177/1534508418777866.

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This study examined the item and category response option functioning of items on the Student Risk Screening Scale for Internalizing and Externalizing Behaviors (SRSS-IE), using item response theory (IRT) methods with a sample of 2,122 middle school students. The SRSS-IE is a screening instrument used to identify students who are potentially at risk for emotional and behavioral disorders (EBD). Utilizing the nominal response and generalized partial credit models of IRT, items from the SRSS-IE were evaluated in terms of the degree to which the response options for each item functioned as intended and how well those response options discriminated among students who exhibited varying levels of EBD risk. Results indicate that the four-response option configuration used in this study may not adequately discriminate regarding the frequency of externalizing and internalizing behaviors demonstrated by middle school students. Recommendations for revising the response options and scoring procedures are discussed.

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Occhino, Filippo. "MARKET SEGMENTATION AND THE RESPONSE OF THE REAL INTEREST RATE TO MONETARY POLICY SHOCKS." Macroeconomic Dynamics 12, no. 5 (November 2008): 591–618. http://dx.doi.org/10.1017/s1365100508070326.

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Following a contractionary monetary policy shock, the aggregate output decreases over time for six to eight quarters, while the real interest rate increases immediately and remains high for three quarters, which can hardly be replicated by models characterized by a standard consumption Euler equation. This paper adopts a segmented markets framework where some households are permanently excluded from financial markets. The aggregate output and the nominal interest rate are modeled as exogenous autoregressive processes, while the real interest rate is determined endogenously. For intermediate levels of market segmentation, the model is able to account for both the persistent decreasing path of the aggregate output and the persistent increase in the real interest rate which follow an unanticipated increase in the nominal interest rate. The sign, the size and the persistence of the responses of the real interest rate and the money growth rate are close to those in the data.

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Richards, Laura J., and Jon T. Schnute. "Use of a General Dose–Response Model for Rockfish Fecundity–Length Relationships." Canadian Journal of Fisheries and Aquatic Sciences 47, no. 6 (June 1, 1990): 1148–56. http://dx.doi.org/10.1139/f90-134.

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In this paper we describe a general method for determining the relationship between fecundity and another fish attribute, such as size or age. Our methods include linear and logarithmic regression models as special cases and are applicable to a wide range of situations. The model we propose is based on the univariate form of the Schnute–Jensen dose–response model. However, we extend the Schnute–Jensen analysis by describing exact inference regions obtained from likelihood contours, to which we assign nominal probability levels. We also provide a method for obtaining an inference band for the predicted curve. We examine the issue of model adequacy as it relates to fecundity–length data from two rockfish (Sebastes) species. We show that the extra complexity of our model is justified, as none of the traditional regression models are appropriate for all three of our data sets. Further, we use inference bands to distinguish fecundity–length relationships for quillback rockfish (S. maliger) from two areas, but we are unable to distinguish one of these relationships from a similar relationship for copper rockfish (S. caurinus).

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Amitrano, Chiara, Giovanni Battista Chirico, Stefania De Pascale, Youssef Rouphael, and Veronica De Micco. "Crop Management in Controlled Environment Agriculture (CEA) Systems Using Predictive Mathematical Models." Sensors 20, no. 11 (May 31, 2020): 3110. http://dx.doi.org/10.3390/s20113110.

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Proximal sensors in controlled environment agriculture (CEA) are used to monitor plant growth, yield, and water consumption with non-destructive technologies. Rapid and continuous monitoring of environmental and crop parameters may be used to develop mathematical models to predict crop response to microclimatic changes. Here, we applied the energy cascade model (MEC) on green- and red-leaf butterhead lettuce (Lactuca sativa L. var. capitata). We tooled up the model to describe the changing leaf functional efficiency during the growing period. We validated the model on an independent dataset with two different vapor pressure deficit (VPD) levels, corresponding to nominal (low VPD) and off-nominal (high VPD) conditions. Under low VPD, the modified model accurately predicted the transpiration rate (RMSE = 0.10 Lm−2), edible biomass (RMSE = 6.87 g m−2), net-photosynthesis (rBIAS = 34%), and stomatal conductance (rBIAS = 39%). Under high VPD, the model overestimated photosynthesis and stomatal conductance (rBIAS = 76–68%). This inconsistency is likely due to the empirical nature of the original model, which was designed for nominal conditions. Here, applications of the modified model are discussed, and possible improvements are suggested based on plant morpho-physiological changes occurring in sub-optimal scenarios.

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