Multiple Approaches to Analyzing Count Data in Studies of Individual Differences : The Prospensity for Type I Errors, Illustrated With The Case of Absenteeism Prediction  

Oleh:

Sturman, Michael C.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Educational and Psychological Measurement vol. 59 no. 3 (1999), page 414-430.
Topik: Prediction; statistical methods; testing; tests
Fulltext: 414.pdf (108.95KB)

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Perpustakaan Pusat (Semanggi) Nomor Panggil: EE30.3 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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The present study compares eight models for analyzing count data : ordinary least squares (OLS), OLS with a transformed dependent variable. Tobit, poisson, over dispersed poisson, negative binomial, orginal logistic, and orginal prohibit regressions. Simulation reveals the extent that each model produces false positives. Results suggest that, despite methodological expectations, OLS regression does not produce more false positives than expected by chance. The tobit and poisson models yield too many false positives. The negative binomial models produce fewer than expected false positives.

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