… of the regression coefficients using Wald tests (z tests used in … Here, significance was
considered with a relaxed value of P<… In summary, two logistic regression methods were …

… categorical? This paper provides an intuitive introduction to logistic regression, the most
appropriate statistical technique … magnitude and to test the coefficients’ statistical significance (p-…

… This chapter examines the multiple ways to interpret effects in logistic regression results. It …
variables, it is of course a single categorical measure. It is important to test for the significance …

… Logistic regression is the commonly used statistical method in empirical studies involving
categorical dependent variables… while the p value of the significance test was reported by most …

… Ordinary logistic regression (OLR) is a technique for modeling … One popular way to assess
fit is by means of significance tests … -level categorical variables, because a categorical variable …

… commonly used categorical data analysis techniques, and … apply to loglinear models (Chapter
7), logistic regression with … - of- fit tests that are used with the subsequent categorical data …

… The current article tests two alternative procedures to LRMs … become a standard procedure
used in the analysis of binary … about covariate adjustment in logistic regression models. …

… , including model fitting, goodness of fit test, and model … Regression analysis, a common
statistical method employed in … ratio of three-level categorical variables, ie, education level. …

… and how to use these regression analysis techniques. The following … For example, logistic
regression analysis can be performed … When these categorical covariates are included in the …

… A logistic regression model was fitted with step‑wise method to the above dataset with …
categorical variables were expressed as proportions and compared with Chi‑square test or Z test …