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Journal articles on the topic 'Effects analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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1

Ayvaz, Serkan, and Mohammed O. Shiha. "The Effects of Emoji in Sentiment Analysis." International Journal of Computer and Electrical Engineering 9, no. 1 (2017): 360–69. http://dx.doi.org/10.17706/ijcee.2017.9.1.360-369.

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2

Sutheebanjard, Phaisarn, and Wichian Premchaiswadi. "Analysis of Calendar Effects: Day-of-the-Week Effect on the Stock Exchange of Thailand (SET)." International Journal of Trade, Economics and Finance 1, no. 1 (2010): 57–62. http://dx.doi.org/10.7763/ijtef.2010.v1.11.

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3

Haleem, Azhar M., Abdul Hameed M, Jawad Al Obaidy, and Ula H. Mahmood. "Microbial Analysis and Cytogenetic Effects of Drinking Bottled Water." Indian Journal of Applied Research 4, no. 6 (2011): 1–3. http://dx.doi.org/10.15373/2249555x/june2014/191.

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4

Anker, Ashley, Amber Marie Reinhart, and Thomas Hugh Feeley. "Meta-Analysis of Meta-Analyses in Communication: Comparing Fixed Effects and Random Effects Analysis Models." Communication Quarterly 58, no. 3 (2010): 257–78. http://dx.doi.org/10.1080/01463373.2010.503154.

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5

Ратовский, Константин, Konstantin Ratovsky, Максим Клименко, et al. "After-effects of geomagnetic storms: statistical analysis and theoretical explanation." Solar-Terrestrial Physics 4, no. 4 (2018): 26–32. http://dx.doi.org/10.12737/stp-44201804.

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Our previous studies have shown the presence of daytime positive electron density disturb-ances during several days after the start of the recovery phase. The aim of this paper is to study after-effects of geomagnetic storms (after-storm effects), i.e. ionospher-ic effects observed on the 3–5th day after the beginning of the storm recovery phase. From numerical calcula-tions with the GSM TIP model, we have found the main mechanisms for the formation of the after-storm effects. Using Irkutsk (52° N, 104° E) and Kaliningrad (54° N, 20° E) ionosonde data, we have carried out a statistical analysi

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6

Čupera, J., F. Bauer, L. Severa, and M. Tatíček. "Analysis of force effects measured in the tractor three-point linkage." Research in Agricultural Engineering 57, No. 3 (2011): 79–87. http://dx.doi.org/10.17221/26/2010-rae.

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The work is focused on description of tractor individual axels and wheels loading during ploughing. A combination of tractor inclination with force and momentum effects need not always result in marked differences in the load of driving wheels. This paper documents the relationship existing between forces working in the upper drawbar F<sub>h</sub> of the three-point linkage and the momentum M<sub>Tx</sub>. It was also demonstrated that with the increasing value of M<sub>Tx</sub> the difference between loads of both rear wheels reduces. The described algorith

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7

Lander, David. "Random-Effects Meta-analysis of Inconsistent Effects." Annals of Internal Medicine 161, no. 5 (2014): 379. http://dx.doi.org/10.7326/l14-5017-7.

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8

Keum, NaNa, Chung-Cheng Hsieh, and Nancy Cook. "Random-Effects Meta-analysis of Inconsistent Effects." Annals of Internal Medicine 161, no. 5 (2014): 379. http://dx.doi.org/10.7326/l14-5017-8.

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9

Cornell, John E. "Random-Effects Meta-analysis of Inconsistent Effects." Annals of Internal Medicine 161, no. 5 (2014): 380. http://dx.doi.org/10.7326/l14-5017-9.

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10

Serghiou, Stylianos, and Steven N. Goodman. "Random-Effects Meta-analysis." JAMA 321, no. 3 (2019): 301. http://dx.doi.org/10.1001/jama.2018.19684.

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11

Jackson, Dan, and Rebecca Turner. "Power analysis for random-effects meta-analysis." Research Synthesis Methods 8, no. 3 (2017): 290–302. http://dx.doi.org/10.1002/jrsm.1240.

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12

Wajahat, Mehreen, Faisal Moeen, Syed Wilayat Husain, Sumera Siddique, and Zohaib Khurshid. "Effects of Various Mouthwashes on the Orthodontic Nickel-Titanium Wires: Corrosion Analysis." Journal of the Pakistan Dental Association 29, no. 01 (2020): 30–37. http://dx.doi.org/10.25301/jpda.291.30.

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13

Choi, Younsun. "Periodic Delay Effects on Cutting Dynamics." Journal of Dynamics and Differential Equations 17, no. 2 (2005): 353–89. http://dx.doi.org/10.1007/s10884-005-3145-y.

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14

Lee, Jung-Gyo. "A Meta-Analysis of Advertising Context Effects in TV Commercials." KOREAN JOURNAL OF ADVERTISING 31, no. 3 (2020): 85–107. http://dx.doi.org/10.14377/kja.2020.4.15.85.

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15

Cai, Hongsheng. "Dispersive Smoothing Effects for KdV Type Equations." Journal of Differential Equations 136, no. 2 (1997): 191–221. http://dx.doi.org/10.1006/jdeq.1996.3245.

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16

Su, Jianzhong. "Effects of periodic forcing on delayed bifurcations." Journal of Dynamics and Differential Equations 9, no. 4 (1997): 561–625. http://dx.doi.org/10.1007/bf02219398.

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17

Hart, V., M. Nentvichová-Hartová, and P. Tauchman. "Analysis of herbicide effects on Douglas fir (Pseudotsuga menziesii [Mirb.] Franco) natural regeneration." Journal of Forest Science 56, No. 5 (2010): 209–17. http://dx.doi.org/10.17221/77/2009-jfs.

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Douglas fir (Pseudotsuga menziesii [Mirb.] Franco) natural regeneration under parent stand after weed suppression was investigated in the area of the Training Forest Enterprise in Kostelec nad Čern&yacute;mi lesy. The study evaluates two measurements made in a two-year interval. The parent stand, where Douglas fir grows in mixture with our domestic tree species, is one of the oldest and most productive stands at the Training Forest Enterprise in Kostelec nad Čern&yacute;mi lesy. Herbicides for the control of weeds were applied onto three permanent experimental plots under the parent st

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18

Nagy, I., J. Sölkner, L. Csató, J. Farkas, and L. Radnóczi. "Analysis of alternative models treating herd × year effects as fixed or random." Czech Journal of Animal Science 49, No. 8 (2011): 349–56. http://dx.doi.org/10.17221/4319-cjas.

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The analysis was conducted of the national database of station tests carried out between May 1996&ndash; February 2001, using the Hungarian Large White breed. Days of test, total amount of consumed feed and valuable cuts were taken into the analysis. Using the method of cross validation, small subsets of the data were excluded and then predicted using the remaining part of the data treating herd &times; year effects either as fixed or as random. The size of the data excluded was 50 or 10 records at a time and the process was repeated 100 or 500 times, respectively. Mean squared error,

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19

Ma, Gang, Liping Sun, Youwei Kang, and Lixin Xu. "Effects of Different Influence Factors on Static and Dynamic Analysis of Mooring Line." International Journal of Engineering and Technology 7, no. 2 (2015): 95–102. http://dx.doi.org/10.7763/ijet.2015.v7.774.

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20

Chandrashekaran, Murali, and Beth A. Walker. "Meta-Analysis with Heteroscedastic Effects." Journal of Marketing Research 30, no. 2 (1993): 246. http://dx.doi.org/10.2307/3172831.

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21

Spineli, Loukia M., and Nikolaos Pandis. "Meta-analysis: Random-effects model." American Journal of Orthodontics and Dentofacial Orthopedics 157, no. 2 (2020): 280–82. http://dx.doi.org/10.1016/j.ajodo.2019.10.007.

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22

King, Donald L. "Context effects: Pervasiveness and analysis." Behavioral and Brain Sciences 15, no. 3 (1992): 570. http://dx.doi.org/10.1017/s0140525x00070084.

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23

Weeks, Sandra Kenney, Feodor Bijkersma, Elizabeth Hubbartt, Bernadette Murphy, and Mary Ann Anderson. "Failure Mode and Effects Analysis." AJN, American Journal of Nursing 104, no. 4 (2004): 72A—72D. http://dx.doi.org/10.1097/00000446-200404000-00030.

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24

Morris, Michael D., and Konan Peck. "Photothermal effects in chemical analysis." Analytical Chemistry 58, no. 7 (1986): 811A—822A. http://dx.doi.org/10.1021/ac00298a002.

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25

Kling, Jeffrey R., Jeffrey B. Liebman, and Lawrence F. Katz. "Experimental Analysis of Neighborhood Effects." Econometrica 75, no. 1 (2007): 83–119. http://dx.doi.org/10.1111/j.1468-0262.2007.00733.x.

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26

COHEN, MICHAEL R., JOHN SENDERS, and NEIL M. DAVIS. "FAILURE MODE AND EFFECTS ANALYSIS." Nursing 24, no. 2 (1994): 40–42. http://dx.doi.org/10.1097/00152193-199402000-00018.

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27

Teng, Sheng‐Hsien (Gary), and Shin‐Yann (Michael) Ho. "Failure mode and effects analysis." International Journal of Quality & Reliability Management 13, no. 5 (1996): 8–26. http://dx.doi.org/10.1108/02656719610118151.

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28

Bernhoeft, N. "Geometrical effects in diffraction analysis." Acta Crystallographica Section A Foundations of Crystallography 55, no. 2 (1999): 274–88. http://dx.doi.org/10.1107/s0108767398008149.

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The use of X-ray and neutron scattering as a tool to study phase transitions is well established. As techniques improve and experiments are made under successively higher resolution, the need to consider the role of both the distribution of diffracting length scales and the incident-beam coherence volume is emphasized. The interplay of diffracting length scales and the beam coherence volume no longer permits calculation of diffraction profiles in terms of the sample intensity response convolved with an instrumental resolution function. Rather, the probe and sample now enter the calculation on

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29

DIXON, M. H. "AN ANALYSIS OF THERMOELECTRIC EFFECTS." Journal of the American Society for Naval Engineers 72, no. 2 (2009): 255–70. http://dx.doi.org/10.1111/j.1559-3584.1960.tb01855.x.

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30

JENAB, K., and B. S. DHILLON. "GROUP-BASED FAILURE EFFECTS ANALYSIS." International Journal of Reliability, Quality and Safety Engineering 12, no. 04 (2005): 291–307. http://dx.doi.org/10.1142/s0218539305001835.

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This paper presents the multi-based experts Failure Effects Analysis (FEA). The experts' opinions differ substantially because the experts do not often agree on the level of the failure factors (failure probability, non-detection probability, severity of effect, and expected cost) and the functions/subsystems attributes (e.g., importance). Therefore, conflict always occurs in Group-based Failure Effects Analysis (GFEA). The approach uses fuzzy Risk Priority Category (RPC) and group decision-making techniques to study both the failure effects on the functions/subsystems and the failure risk cat

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31

Krafty, R. T., M. Hall, and W. Guo. "Functional mixed effects spectral analysis." Biometrika 98, no. 3 (2011): 583–98. http://dx.doi.org/10.1093/biomet/asr032.

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32

Zeng, D., and D. Y. Lin. "On random-effects meta-analysis." Biometrika 102, no. 2 (2015): 281–94. http://dx.doi.org/10.1093/biomet/asv011.

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33

Scheiner, Samuel M. "Affinity analysis: effects of sampling." Vegetatio 86, no. 2 (1990): 175–81. http://dx.doi.org/10.1007/bf00031733.

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34

Fletcher, Carol E. "Failure Mode and Effects Analysis." Journal of Nursing Administration 27, no. 12 (1997): 19–26. http://dx.doi.org/10.1097/00005110-199712000-00008.

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35

White, Ian R. "Multivariate Random-effects Meta-analysis." Stata Journal: Promoting communications on statistics and Stata 9, no. 1 (2009): 40–56. http://dx.doi.org/10.1177/1536867x0900900103.

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36

Kontopantelis, Evangelos, and David Reeves. "Metaan: Random-effects Meta-analysis." Stata Journal: Promoting communications on statistics and Stata 10, no. 3 (2010): 395–407. http://dx.doi.org/10.1177/1536867x1001000307.

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37

Ashley, Laura, and Gerry Armitage. "Failure Mode and Effects Analysis." Journal of Patient Safety 6, no. 4 (2010): 210–15. http://dx.doi.org/10.1097/pts.0b013e3181fc98d7.

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38

Mikkelsen, S., J. P. Bonde, and J. H. Andersen. "Analysis of job strain effects." Occupational and Environmental Medicine 68, no. 10 (2011): 786. http://dx.doi.org/10.1136/oemed-2011-100203.

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39

Krämer, Benjamin, and Christina Peter. "Exemplification Effects: A Meta-Analysis." Human Communication Research 46, no. 2-3 (2020): 192–221. http://dx.doi.org/10.1093/hcr/hqz024.

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Abstract The presentation of single cases as examples for larger phenomena has a long-standing tradition in journalism. However, their usage has been viewed rather critically within the scientific community, because they are employed in a highly selective manner. Consequently, over the course of the last three decades, communication scholars from different research traditions have concerned themselves with the question of how single-case information within media content affects audience judgments. Although most publications report exemplification effects of some sort, it remains unclear which

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40

Chandukala, Sandeep R., Jeffrey P. Dotson, Jeff D. Brazell, and Greg M. Allenby. "Bayesian Analysis of Hierarchical Effects." Marketing Science 30, no. 1 (2011): 123–33. http://dx.doi.org/10.1287/mksc.1100.0602.

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41

Saleh, N. S., K. A. Al-Saleh, and A. J. Abu El-Haija. "Enhancement effects in XRF analysis." Journal of Radioanalytical and Nuclear Chemistry Articles 120, no. 1 (1988): 161–65. http://dx.doi.org/10.1007/bf02037863.

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42

Dungan, D. Peter, and Thomas A. Wilson. "Macroeconomic effects and sensitivity analysis." Journal of Policy Modeling 13, no. 3 (1991): 435–57. http://dx.doi.org/10.1016/0161-8938(91)90025-t.

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43

Casciati, F., and L. Faravelli. "Randomness effects in crashworthiness analysis." International Journal of Non-Linear Mechanics 26, no. 6 (1991): 827–34. http://dx.doi.org/10.1016/0020-7462(91)90034-q.

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44

Feagin, R. A., X. B. Wu, and T. Feagin. "Edge effects in lacunarity analysis." Ecological Modelling 201, no. 3-4 (2007): 262–68. http://dx.doi.org/10.1016/j.ecolmodel.2006.09.019.

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45

Jain, N. C. "Matrix effects in auger analysis." Journal of Electron Spectroscopy and Related Phenomena 43, no. 2 (1987): C1—C3. http://dx.doi.org/10.1016/0368-2048(87)80030-0.

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46

Chandrashekaran, Murali, and Beth A. Walker. "Meta-Analysis with Heteroscedastic Effects." Journal of Marketing Research 30, no. 2 (1993): 246–55. http://dx.doi.org/10.1177/002224379303000209.

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To enhance the utility of meta-analysis as an integrative tool for marketing research, heteroscedastic MLE (HMLE), a maximum-likelihood-based estimation procedure, is proposed as a method that overcomes heteroscedasticity, a problem known to impair OLS estimates and threaten the validity of meta-analytic findings. The results of a Monté Carlo simulation experiment reveal that, under a wide range of heteroscedastic conditions, HMLE is more efficient and powerful than OLS and achieves these performance advantages without inflating type I error. Further, the relative performance of HMLE increases

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47

Hayat, T., M. Javed, and S. Asghar. "Slip effects in peristalsis." Numerical Methods for Partial Differential Equations 27, no. 5 (2010): 1003–15. http://dx.doi.org/10.1002/num.20564.

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48

Du, Yihong. "Effects of a Degeneracy in the Competition Model." Journal of Differential Equations 181, no. 1 (2002): 92–132. http://dx.doi.org/10.1006/jdeq.2001.4074.

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49

Du, Yihong. "Effects of a Degeneracy in the Competition Model." Journal of Differential Equations 181, no. 1 (2002): 133–64. http://dx.doi.org/10.1006/jdeq.2001.4075.

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50

Donato, Michele, Zhonghui Xu, Alin Tomoiaga, et al. "Analysis and correction of crosstalk effects in pathway analysis." Genome Research 23, no. 11 (2013): 1885–93. http://dx.doi.org/10.1101/gr.153551.112.

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