Relevant bibliographies by topics / Misclassification adjustment

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  1. Journal articles
  2. Dissertations / Theses
  3. Books

Academic literature on the topic 'Misclassification adjustment'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 February 2022

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Journal articles on the topic "Misclassification adjustment"

1

Stewart, Susan L., Karen C. Swallen, Sally L. Glaser, Pamela L. Horn-Ross, and Dee W. West. "Adjustment of Cancer Incidence Rates for Ethnic Misclassification." Biometrics 54, no. 2 (1998): 774. http://dx.doi.org/10.2307/3109783.

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2

Gustafson, Paul, and Sander Greenland. "Curious phenomena in Bayesian adjustment for exposure misclassification." Statistics in Medicine 25, no. 1 (2005): 87–103. http://dx.doi.org/10.1002/sim.2341.

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3

Sun, Liangrui, Michelle Xia, Yuanyuan Tang, and Philip G. Jones. "Bayesian adjustment for unidirectional misclassification in ordinal covariates." Journal of Statistical Computation and Simulation 87, no. 18 (2017): 3440–68. http://dx.doi.org/10.1080/00949655.2017.1370649.

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4

Vogel, C., and O. Gefeller. "Implications of Nondifferential Misclassification on Estimates of Attributable Risk." Methods of Information in Medicine 41, no. 04 (2002): 342–48. http://dx.doi.org/10.1055/s-0038-1634392.

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Summary Objectives: Only the effects of isolated nondifferential misclassification of exposure or disease on the estimates of attributable risk have been discussed in the literature. The aim of this paper is to broaden the spectrum of scenarios for which implications of misclassification are available. Methods: For this purpose, a matrix-based approach allowing a comprehensive, unified analysis of various structures of misclassification is introduced. The relative bias or – in the situation of covariate misclassification – the relative adjustment are presented for the different misclassificati
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Chu, Rong, Paul Gustafson, and Nhu Le. "Bayesian adjustment for exposure misclassification in case-control studies." Statistics in Medicine 29, no. 9 (2010): 994–1003. http://dx.doi.org/10.1002/sim.3829.

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6

Tran, Nguyen, Neal Goldstein, and Seth Welles. "Bias Adjustment Techniques Are Underutilized in HIV Sexual Risk Estimation: A Systematic Review." International Journal of Environmental Research and Public Health 15, no. 8 (2018): 1696. http://dx.doi.org/10.3390/ijerph15081696.

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Background: Valid measurement of determinants of HIV infection among men who have sex with men (MSM) is critical for intervention planning and resource allocation. However, sexual minority research concerning HIV risk often relies on proxy exposures of sexual behaviors such as sexual orientation and partner gender. Inferring high risk sexual behaviors (i.e., condomless anal intercourse) from these proxies inaccurately captures HIV risk, but few studies have attempted to correct for this bias. Methods: We performed a systematic review of methodological practices for estimating risk of HIV infec
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7

Blouin, Brittany, Martin Casapia, Jay S. Kaufman, Lawrence Joseph, Charles Larson, and Theresa W. Gyorkos. "Bayesian Methods for Exposure Misclassification Adjustment in a Mediation Analysis." Epidemiology 30, no. 5 (2019): 659–68. http://dx.doi.org/10.1097/ede.0000000000001051.

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Pourhoseingholi, Mohamad Amin, Setareh Akbari, and Ahmad Reza Baghestani. "MISCLASSIFICATION IN CANCER REGISTRATION AND BAYESIAN ADJUSTMENT: A SIMULATION STUDY." JP Journal of Biostatistics 16, no. 2 (2019): 91–100. http://dx.doi.org/10.17654/bs016020091.

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9

Ng, Derek K., Alison G. Abraham, Alden L. Gross, and Stephen R. Hooper. "Re: Bayesian Methods for Exposure Misclassification Adjustment in a Mediation Analysis." Epidemiology 31, no. 5 (2020): e41-e42. http://dx.doi.org/10.1097/ede.0000000000001213.

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10

Liu, Xinhua, and Kung-Yee Liang. "Adjustment for non-differential misclassification error in the generalized linear model." Statistics in Medicine 10, no. 8 (1991): 1197–211. http://dx.doi.org/10.1002/sim.4780100804.

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Dissertations / Theses on the topic "Misclassification adjustment"

1

Chu, Rong. "Bayesian adjustment for exposure misclassification in case-control studies." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/32108.

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Measurement error occurs frequently in observational studies investigating the relationship between exposure variables and the clinical outcome. Error-prone observations on the explanatory variable may lead to biased estimation and loss of power in detecting the impact of an exposure variable. The mechanism of measurement error, such as whether or in what way the quality of data is affected by the disease status, is seldom completely revealed to the investigators. This increases uncertainty in assessing the consequences of ignoring measurement error associated with observed data, and bri
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2

Cormier, Eric. "Time-varying exposure subject to misclassification : bias characterization and adjustment." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/27839.

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Measurement error occurs frequently in observational studies investigating the relationship between exposure variables and a clinical outcome. Error-prone observations on the explanatory variable may lead to biased estimation and loss of power in detecting the impact of an exposure variable. When the exposure variable is time-varying, the impact of misclassification is complicated and significant. This increases uncertainty in assessing the consequences of ignoring measurement error associated with observed data, and brings difficulties to adjustment for misclassification. In this study we co
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3

He, Fei. "Novel statistical models for ecological momentary assessment studies of sexually transmitted infections." Diss., 2016. http://hdl.handle.net/1805/11288.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>The research ideas included in this dissertation are motivated by a large sexually trans mitted infections (STIs) study (IU Phone study), which is also an ecological momentary assessment (EMA) study implemented by Indiana University from 2008 to 2013. EMA, as a group of methods used to collect subjects’ up-to-date behaviors and status, can increase the accuracy of this information by allowing a participant to self-administer a survey or diary entry, in their own environment, as close to the occurrence of the behavior as possible
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Books on the topic "Misclassification adjustment"

1

Elwood, Mark. Error and bias in observations. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199682898.003.0006.

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This chapter distinguishes error and bias, non-differential and differential misclassification distinguished. Non-differential misclassification almost always biases results toward the null, while differential misclassification can affect results in any direction. Methods to minimise observation bias include single, double and triple blind assessment. It discusses recall and other biases, with methods of assessment and avoidance, and practical issues on reducing error and bias. In part two, it shows how to measure and adjust for observational error and bias, including Kappa and adjusting for n
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2

Gustafson, Paul. Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments. Chapman & Hall/CRC, 2003.

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