2015
DOI: 10.1177/0962280215572407
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Sample size determination for logistic regression on a logit-normal distribution

Abstract: Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination (Rcov2) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal (LN) distribution which can be generated from a logistic transformation of a normal distribu… Show more

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Cited by 14 publications
(10 citation statements)
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“…A recent statistical paper presents findings that the sample size for multivariable logistic regression can be determined using information on outcome measures [20]. Additionally, a previous study revealed that events per variable values of 10 or greater indicate no major problems [21].…”
Section: Design Settings and Participantsmentioning
confidence: 99%
“…A recent statistical paper presents findings that the sample size for multivariable logistic regression can be determined using information on outcome measures [20]. Additionally, a previous study revealed that events per variable values of 10 or greater indicate no major problems [21].…”
Section: Design Settings and Participantsmentioning
confidence: 99%
“…In addition to repeated measures of Cobb angles (raw value), we adopted a logistic regression analysis to investigate the correlation of curve pattern with scoliosis progression after 2 years of PSSE using a clinical significance threshold (D-value of a change in Cobb angle: ≥ 6 degrees). This showed a value of clinical practice, but the analysis was underpowered regarding the small sample size [ 53 ]. Thus, a study with a bigger sample size is required to detect the correlation of curve pattern with scoliosis progression after PSSE treatment.…”
Section: Discussionmentioning
confidence: 99%
“…Kegunaan dari regresi logistik adalah untuk menguji setiap kemungkinan yang terjadi dengan adanya variabel terikat. Kemungkinan ini dapat diprediksi melalui serangkaian variabel bebas (Hemmert, Schons, Wieseke, & Schimmelpfennig, 2018;Kim, Heath, & Heilbrun, 2017;Simmonds & Higgins, 2016).…”
Section: Metodeunclassified