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Douglas G Bonett

Publications and source records attributed to Douglas G Bonett.

5 recordsLinked to original sources
PubMed2006

Confidence intervals for a ratio of binomial proportions based on paired data.

Four interval estimation methods for the ratio of marginal binomial proportions are compared in terms of expected interval width and exact coverage probability. Two new methods are proposed that are based on combining two Wilson score intervals. The new methods are easy to compute and perform as well or better than the method recently proposed by Nam and Blackwelder. Two sample size formulas are proposed to approximate the sample size required to achieve an interval estimate with desired confidence level and width.

Adolescent↗
PubMed2002

The moderating effects of employee tenure on the relation between organizational commitment and job performance: a meta-analysis.

This meta-analysis investigated the correlation between attitudinal commitment and job performance for 3,630 employees obtained from 27 independent studies across various levels of employee tenure. Controlling for employee age and other nuisance variables, the authors found that tenure had a very strong nonlinear moderating effect on the commitment-performance correlation, with correlations tending to decrease exponentially with increasing tenure. These findings do not appear to be the result of differences across studies in terms of the type of performance measure (supervisory vs. self), type of tenure (job vs. organizational), or commitment measure (Organizational Commitment Questionnaire [L. W. Porter, R. M. Steers, R. T. Mowday, & P. V. Boulian, 19741 vs. other). The implications and future research directions of these results are discussed.

Adult↗
PubMed2002

Statistical inference for a linear function of medians: confidence intervals, hypothesis testing, and sample size requirements.

When the distribution of the response variable is skewed, the population median may be a more meaningful measure of centrality than the population mean, and when the population distribution of the response variable has heavy tails, the sample median may be a more efficient estimator of centrality than the sample mean. The authors propose a confidence interval for a general linear function of population medians. Linear functions have many important special cases including pairwise comparisons, main effects, interaction effects, simple main effects, curvature, and slope. The confidence interval can be used to test 2-sided directional hypotheses and finite interval hypotheses. Sample size formulas are given for both interval estimation and hypothesis testing problems.

Humans↗