Hi, I run a chi-square test. My codes are below: proc format; value $category '' ='' 'Agree'='Agree1' 'Disagree'= 'Disagree1' 'Neither agree or disagree'='Neither agree or disagree1' 'Strongly agree'= 'Agree1' 'Strongly disagree'= 'Disagree1' ; proc freq data=red.survey2; tables My_compensation_should_be_augmen*Program__select_one_ /chisq exact ; format My_compensation_should_be_augmen $category. ; run; I received following output: Table of My_compensation_should_be_augmen by Program__select_one_ My_compensation_should_be_augmen(My compensation should be augmented due to the associated risks) Program__select_one_(Program: select one#) Frequency Percent Row Pct Col Pct Anesthesia Emergency Medicine General Surgery Total Agree1 28 19.05 32.56 49.12 24 16.33 27.91 82.76 34 23.13 39.53 55.74 86 58.50 Disagree1 12 8.16 54.55 21.05 1 0.68 4.55 3.45 9 6.12 40.91 14.75 22 14.97 Neither agree or disagree1 17 11.56 43.59 29.82 4 2.72 10.26 13.79 18 12.24 46.15 29.51 39 26.53 Total 57 38.78 29 19.73 61 41.50 147 100.00 Frequency Missing = 4   Statistic DF Value Prob Chi-Square 4 10.0471 0.0396 Likelihood Ratio Chi-Square 4 11.1415 0.0250 Mantel-Haenszel Chi-Square 1 0.1559 0.6929 Phi Coefficient   0.2614   Contingency Coefficient   0.2529   Cramer's V   0.1849       I get a p-value of 0.0396. This shows me that My_compensation_should_be_augmen is significantly different by the program. However, it does not give me  what is specifically different here significantly. I want to say something like respondents who agreed were significantly higher in Emergency Medicine than Anesthesia or may be respondents who agreed were significantly higher in Emergency Medicine than Anesthesia and Surgery. I am not sure which statement is correct. How can i do that?   Thanks,   ... View more

Hi,   I have a linear regression model Proc GLM where my outcome is medication dose prescribed and variables being studied are patient gender, physician gender, their interarction term and there are few more variables.   Proc GLM gives significant p-value for the main effects and interaction both.   Medication dose dispensed= 232.65 +8.7 Male patient +23.3 female surgeon + 8.83 Male patient*female surgeon   Please let me know how to interpret association of patient gender and surgeon gender with continuous outcome( medication dispensed). Thanks,     ... View more

Hi, I am creating a bar chart but would like to get percentage rather than frequency. And percentage i am interested in is not percentage of total frequency but percentage of group frequency. My SAS code is like below:   ods graphics on; proc sgplot data=red.survey2; vbar I_feel_well_informed_about_the_C /group=Program__select_one_ groupdisplay=cluster ; format I_feel_well_informed_about_the_C $category. ; run;   And results are attached. I am interested in percentage rather than frequency in y axis.  I a way for the group agree it sums to 100% , for disagree it sums to 100%.   Thanks,                         ... View more