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Determining Sample Size in Logistic Regression with G-Power

Year 2019, Volume: 2 Issue: 1, 16 - 22, 01.01.2019
https://izlik.org/JA59ZH83NM

Abstract

There
are several methods used to determine the sample size. Investigator; because of
the insufficient precious resources such as time, labor, money, tools and
equipment, it works by pulling the sample with a suitable sampling method from
the population it is examining. According to the statistics obtained from the
sample, he will make comments about the population and make decisions. The
correctness of the decisions made is closely related to the size of the sample.
For this reason, the problem of determining sample size is one of the first and
important problems of an investigator. A small sample of information causes
loss of information and misjudgments. A very large sample is contrary to the
purpose of sampling and resources are wasted. The calculation of the sample
size can now be done very easily via free programs.

References

  • Buse A. 1982. The likelihood ratio, wald and lagran ge multiplier tests: an expository note. the american statistician, 36(3): 1.
  • Demidenko E. 2007. Sample size determination for logistic regression revisited, Statist Med, 26: 3385-3397.
  • Erdfelder E, Faul F, Buchner A. 1996. Gpower: A general power analysis. Behavior Research Methods, Instruments, & Computer, 28: 1-11.
  • Faul F, Erdfelder E, Buchner A, Lang AG. 2009. Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behavior Resarch Methods, 41: 1149-1160.
  • Herrera AN, Gomez J. 2008. Influence of equal or unequal comparison group sample sizes on the detection of differential item functioning using the Mantel–Haenszel and logistic regression techniques. Quality & Quantity, 42: 739–755.
  • Hsieh FY, Bloch DA, Larsen MD. 1998. A simple method of sample size calculation for linear and logistic regression. Statis Med, 17: 1623-1634.
  • Lyles RH, Lin HM, Williamson JM. 2007. A practial approach to computing power for generalized linear models with nominal, count, or ordinal responses. Statis Med, 26: 1632-1648.
  • Nemes S, Jonasson JM, Genel A, Steineck G. 2009. Bias in odds ratios by logistic regression modelling and sample size, BMC Medical Research Methodology, 9(56): 1-5.
  • Moineddin R, Matheson FI, Glazier RH. 2007. A simulation study of sample size for multilevel logistic regression models, BMC Medical Research Methodology, 4(34): 1-10.
  • Şahin M. 1999. Lojistik Regresyon ve Biyolojik Alanlarda Kullanımı. Yüksek Lisans Tezi. Kahramanmaraş Sütçü İmam Üniversitesi Fen Bilimleri Enstitüsü Zootekni Ana Bilim Dalı. Kahramanmaraş.
  • Whittemore AS. 1981. Sample size for logistic regression with small response probabilities. JASA, 76: 27-32.

DETERMINING SAMPLE SIZE IN LOGISTIC REGRESSION WITH G-POWER

Year 2019, Volume: 2 Issue: 1, 16 - 22, 01.01.2019
https://izlik.org/JA59ZH83NM

Abstract

References

  • Buse A. 1982. The likelihood ratio, wald and lagran ge multiplier tests: an expository note. the american statistician, 36(3): 1.
  • Demidenko E. 2007. Sample size determination for logistic regression revisited, Statist Med, 26: 3385-3397.
  • Erdfelder E, Faul F, Buchner A. 1996. Gpower: A general power analysis. Behavior Research Methods, Instruments, & Computer, 28: 1-11.
  • Faul F, Erdfelder E, Buchner A, Lang AG. 2009. Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behavior Resarch Methods, 41: 1149-1160.
  • Herrera AN, Gomez J. 2008. Influence of equal or unequal comparison group sample sizes on the detection of differential item functioning using the Mantel–Haenszel and logistic regression techniques. Quality & Quantity, 42: 739–755.
  • Hsieh FY, Bloch DA, Larsen MD. 1998. A simple method of sample size calculation for linear and logistic regression. Statis Med, 17: 1623-1634.
  • Lyles RH, Lin HM, Williamson JM. 2007. A practial approach to computing power for generalized linear models with nominal, count, or ordinal responses. Statis Med, 26: 1632-1648.
  • Nemes S, Jonasson JM, Genel A, Steineck G. 2009. Bias in odds ratios by logistic regression modelling and sample size, BMC Medical Research Methodology, 9(56): 1-5.
  • Moineddin R, Matheson FI, Glazier RH. 2007. A simulation study of sample size for multilevel logistic regression models, BMC Medical Research Methodology, 4(34): 1-10.
  • Şahin M. 1999. Lojistik Regresyon ve Biyolojik Alanlarda Kullanımı. Yüksek Lisans Tezi. Kahramanmaraş Sütçü İmam Üniversitesi Fen Bilimleri Enstitüsü Zootekni Ana Bilim Dalı. Kahramanmaraş.
  • Whittemore AS. 1981. Sample size for logistic regression with small response probabilities. JASA, 76: 27-32.
There are 11 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Article
Authors

Aysel Yenipınar

Şeyma Koç

Demet Çanga

Fahrettin Kaya

Submission Date October 11, 2018
Acceptance Date November 23, 2018
Publication Date January 1, 2019
IZ https://izlik.org/JA59ZH83NM
Published in Issue Year 2019 Volume: 2 Issue: 1

Cite

APA Yenipınar, A., Koç, Ş., Çanga, D., & Kaya, F. (2019). Determining Sample Size in Logistic Regression with G-Power. Black Sea Journal of Engineering and Science, 2(1), 16-22. https://izlik.org/JA59ZH83NM
AMA 1.Yenipınar A, Koç Ş, Çanga D, Kaya F. Determining Sample Size in Logistic Regression with G-Power. BSJ Eng. Sci. 2019;2(1):16-22. https://izlik.org/JA59ZH83NM
Chicago Yenipınar, Aysel, Şeyma Koç, Demet Çanga, and Fahrettin Kaya. 2019. “Determining Sample Size in Logistic Regression With G-Power”. Black Sea Journal of Engineering and Science 2 (1): 16-22. https://izlik.org/JA59ZH83NM.
EndNote Yenipınar A, Koç Ş, Çanga D, Kaya F (January 1, 2019) Determining Sample Size in Logistic Regression with G-Power. Black Sea Journal of Engineering and Science 2 1 16–22.
IEEE [1]A. Yenipınar, Ş. Koç, D. Çanga, and F. Kaya, “Determining Sample Size in Logistic Regression with G-Power”, BSJ Eng. Sci., vol. 2, no. 1, pp. 16–22, Jan. 2019, [Online]. Available: https://izlik.org/JA59ZH83NM
ISNAD Yenipınar, Aysel - Koç, Şeyma - Çanga, Demet - Kaya, Fahrettin. “Determining Sample Size in Logistic Regression With G-Power”. Black Sea Journal of Engineering and Science 2/1 (January 1, 2019): 16-22. https://izlik.org/JA59ZH83NM.
JAMA 1.Yenipınar A, Koç Ş, Çanga D, Kaya F. Determining Sample Size in Logistic Regression with G-Power. BSJ Eng. Sci. 2019;2:16–22.
MLA Yenipınar, Aysel, et al. “Determining Sample Size in Logistic Regression With G-Power”. Black Sea Journal of Engineering and Science, vol. 2, no. 1, Jan. 2019, pp. 16-22, https://izlik.org/JA59ZH83NM.
Vancouver 1.Yenipınar A, Koç Ş, Çanga D, Kaya F. Determining Sample Size in Logistic Regression with G-Power. BSJ Eng. Sci. [Internet]. 2019 Jan. 1;2(1):16-22. Available from: https://izlik.org/JA59ZH83NM

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