JSTOR Daily

Differential Item Functioning Analysis With Ordinal Logistic Regression Techniques: DIFdetect and difwithpar

Introduction: We present an ordinal logistic regression model for identification of items with differential item functioning (DIF) and apply this model to a Mini-Mental State Examination (MMSE) ...
Baseball Prospectus

Caught Looking: Building A Better Run Expectancy Matrix

Caught Looking examines articles from the academic literature relevant to baseball and statistical analysis. This review looks at the inaugural article from the Journal of Sports Analytics, written by ...
technologynetworks

Logistic Regression

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...
JSTOR Daily

Power analysis for trend in ordinal cover classes: implications for long-term vegetation monitoring

Journal of Vegetation Science, Vol. 21, No. 6 (December 2010), pp. 1152-1161 (10 pages) Question: We provide a method to calculate the power of ordinal regression models for detecting temporal trends ...
Visual Studio Magazine

Logistic Regression Using PyTorch with L-BFGS

Dr. James McCaffrey of Microsoft Research demonstrates applying the L-BFGS optimization algorithm to the ML logistic regression technique for binary classification -- predicting one of two possible ...