Abstract

Abstract We performed a Monte Carlo computer simulation of the Walker‐Duncan logistic regression technique in a typical epidemiologic prospective setting and analysed the results with respect to the accuracy and reliability of the regression estimates and the associated statistical significance tests ( Z ‐tests). The results strongly suggest that the estimates were neither accurate nor reliable. The magnitude of the difference between the average estimated regression coefficient and its true population value did not necessarily decrease as the sample size increased. The average estimated standard deviation of the estimate of the regression coefficient either overestimated or underestimated the actual standard deviation, the former occurring most, but not all, of the time. The significance tests (a two‐tailed Z ‐test with a significance level of 0.05) had actual type I errors ranging from 0.00 to 0.24 for different samples. This approach is therefore inadequate as an epidemiologic tool for analysis of a Framingham‐type prospective study. Further simulation studies are indicated.

Keywords

StatisticsLogistic regressionStandard deviationRegression dilutionRegression analysisStandard errorMathematicsPopulationStatistical significanceEconometricsMedicineNonlinear regression

Affiliated Institutions

Related Publications

Publication Info

Year
1984
Type
article
Volume
3
Issue
1
Pages
15-26
Citations
7
Access
Closed

External Links

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

7
OpenAlex

Cite This

David E. Lilienfeld, David A. Pyne (1984). The logistic analysis of epidemiologic prospective studies: Investigation by simulation. Statistics in Medicine , 3 (1) , 15-26. https://doi.org/10.1002/sim.4780030104

Identifiers

DOI
10.1002/sim.4780030104