# Applied Logistic Regression Analysis (Quantitative by Scott Menard

By Scott Menard

Emphasizing the parallels among linear and logistic regression, Scott Menard explores logistic regression research and demonstrates its usefulness in interpreting dichotomous, polytomous nominal, and polytomous ordinal based variables. The ebook is geared toward readers with a historical past in bivariate and a number of linear regression.

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Bk = 0. For OLS linear regression, the F ratio with N cases and k independent variables can be calculated as F = [SSR/k]/[SSE/(N k 1)] = (N k 1)SSR/(k)SSE. The attained statistical significance (p) associated with the F ratio indicates the probability of obtaining an R2 as large as the observed R2, or b coefficients as large as the observed b coefficients, if the null hypothesis is true. 05, but other values of p may be chosen), then we reject the null hypothesis and conclude that there is a relationship between the independent variables and the dependent variable that cannot be attributed to chance.

43-47). 2, there was some evidence of nonlinearity in the relationship between frequency of marijuana use and exposure to delinquent friends. One possible transformation that could be used to model this nonlinearity is a logarithmic transformation 6 of the dependent variable, FRQMRJ5. This is done by adding 1 to FRQMRJ5 and then taking the natural logarithm. 72 is the base of the natural logarithm. 32. 1, it is evident that the slope is still positive but the numerical value of the slope has changed (because the units in which the dependent variable is measured have changed from frequency to logged frequency).

Bk = 0. For OLS linear regression, the F ratio with N cases and k independent variables can be calculated as F = [SSR/k]/[SSE/(N k 1)] = (N k 1)SSR/(k)SSE. The attained statistical significance (p) associated with the F ratio indicates the probability of obtaining an R2 as large as the observed R2, or b coefficients as large as the observed b coefficients, if the null hypothesis is true. 05, but other values of p may be chosen), then we reject the null hypothesis and conclude that there is a relationship between the independent variables and the dependent variable that cannot be attributed to chance.