I am new to logistic and GLM procedures, and therefore I have some syntactical and conceptual questions: I have a dataset(attached to this post) which has information about the salary and various other important characteristics of all faculty (n=52) in a college. The descriptions of the variables are as follows: OBS: observation # SX: sex (0=Male, 1=Female) RK: rank (1=Assistant Professor, 2=Associate Professor, 3=Full Professor) YR: # years in current rank DG: highest degree (0=Masters, 1=Doctorate) YD: # years since highest degree earned SL: academic year salary ($) I need to determine if gender is associated with rank, highest degree, number of years in current rank, number of years since highest degree earned, and academic year salary. Since my gender is a binary outcome, I have used logistic regression to address the question. However I am getting a result where all my predictors seem highly significant which does not look to be correct. Am I approaching this question correctly or is my syntax not correct? Should I be using GLM? My code is as follows: proc logistic data=discrimination; freq yd; freq yr; class rk dg; model sx(descending) =rk yr dg yd sl; run; Another question that I am addressing is: 2. Is there a significant relationship between rank and academic year salary? I am using a simple regression model. Here I have assigned rank as X (categorical) and salary as Y(continuous). Am I doing this correctly? Below is the code: proc reg data=discrimination SIMPLE; model SL = rk; run; Thanks in advance for your suggestions!
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