Logits, Probits, and Multinomial Logits
Richard J. Butler,
Matthew J. Butler and
Barbara L. Wilson
Chapter 14 in Advanced Statistics for Health Research, 2023, pp 229-244 from World Scientific Publishing Co. Pte. Ltd.
Abstract:
The following sections are included:BackgroundMaximum likelihood estimation (MLE)Kelly Gee and Butler (2021). Impact of nurseburnout on organizational and position turnoverShields and Ward (2001). Improving nurse retention in the National Health Service in England: The impact of job satisfaction on intentions to quitKwak and Clayton-Matthews (2002). Multinomial logistic regression. Nursing Research, 51(6), 404–410References
Keywords: Nursing; Physician; Healthcare; Public Health; Regression; Orthogonal Projection; Geometric View of Causal Inference; 2SLS; Two-Stage Least Squares; Instrumental Variables; Probits; Logits; Proportional Hazards; Cox Regressions; Quantile Regression; Random Forest Regression; Randomization; Matching; Propensity-Score; Differences-in-Differences; Regression Discontinuity; Fixed Effects; R; SAS; STATA; Research Examples; Empirical Rule; Applied Statistics; Confidence Intervals; VIF; Standard Beta; Histograms; Scatterplots; Regression Gini Index; COVID-19; Gender Wage Differentials; LASSO; Area Under The Curve; AUC; ROC; Decision Trees; Maximum Likelihood; GMM; Data Generating Process; Split Sample Instrumental Variables; Local Average Treatment Effects (LATE); Data Visualization; Omitted Variable Bias; Simultaneous Equations; Measurement Error; Supervised Machine Learning; Panel Data; RGI; Health Professionals (search for similar items in EconPapers)
JEL-codes: C1 I11 I15 (search for similar items in EconPapers)
Date: 2023
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