Table 5.

Multivariate Regressions Predicting Self-Report of Health Problems among Categories with More Than One Correlate

Variance Accounted For (%)β*P
Organic/major problems
Survivors (n = 156)
Total model22.00
Age0.15.04
Sex0.14.07
Treatment intensity0.38.00
Controls (n = 138)
Total model9.00
Minority status−0.12.03
Sex0.18.00
Constitutional/other problems
Survivors (n = 156)
Step 1§11.00
Age0.21.01
Treatment intensity0.25.00
Step 27.00
Lymphoma0.13.13
Solid tumor0.27.00
• * β is standardized.

• Age and treatment intensity are entered as continuous variables to facilitate easier interpretation and to maximize variance of these variables. Thus, positive β values indicate that problems increase with higher age and higher treatment intensity.

• Dichotomous variables are coded as 0 and 1. In particular, sex is coded as 0 = male, 1 = female and minority status is coded as 0 = white and 1 = minority. Thus, a positive β value for sex indicates a positive relationship between female sex and problem reporting. The negative β value for minority status indicates a positive relationship between being white and report of problems.

• § Two steps were used in the regression predicting Constitutional/Other problems in order to determine the unique contribution of diagnosis given the multiple categories in this variable.

• Dummy codes for diagnosis were used to reflect categories of diagnoses of lymphoma and solid tumor.