1. Mental Health Study Example Alachua County, Florida Purpose: Relate mental impairment to two explanatory variables, the severity of life and socioeconomic status

2. The Dataset Subject: a randomly assigned id number (1, 2, 3,…) Mental impairment: ordinal response with categories well, mild symptom formation, moderate symptom formation, and impaired Life events: a composite measure of the number and severity of important life events such as birth of a child, new job, divorce in the family that occurred to the subject within the past three years (0, 1,…,9) Socioeconomic status (SES): measured here as binary (1 = high and 2 = low)

3. The Main Effects Model Proportional odds model J = 4 response categories (well, mild, moderate, impaired) x 1 = life events (0,1,2,…,9) x 2 = SES (1 = low, 2 = high)

4. SAS Code & Output ParameterEstimate Intercept1-0.2819 Intercept2 1.2128 Intercept3 2.2094 life-0.3189 ses 1.1112 proc genmod data=mental; model mental = life ses / dist=multinomial link=clogit; run;

5. What does this mean? and The cumulative probability of starting at the well end of the scale decreases (  1 ) as the life events score increases and also increases at the higher level of SES (  2 ).

6. SES Effect for x 1 = 4.275, the mean life events score THIS WILL BE P(Y < 2) FORMULA P(Y=1) x 2 = 0 (Low SES).16 x 1 = 1 (High SES).37

7. Life Events Effect for x 2 = 1, high SES P(Y=1) x 1 = 2.0 (Lower quartile of life events).55 x 1 = 6.5 (Upper quartile of life events).22 for x 2 = 0, low SES P(Y=1) x 1 = 2.0 (Lower quartile of life events).28 x 1 = 6.5 (Upper quartile of life events).09