I have a data set of patients who were operated on at two different hospitals, A and B. Lymph nodes were removed from each patient during the operation and counted, this is saved as
LN_reviewed for each patient. I want to know how much variability there is in the lymph node number that is not accounted for by gender, the year of the operation, or the age of the patient when operated on. My assumption (hypothesis) is that any additional variability is likely due to the pathologist at the institution (this was not actually measured in my study).
What is the best way to go about estimating the variability in lymph node number that is not accounted for by gender (a factor), year (a continuous variable), or age (a continuous variable)?
My initial attempt at answering this question
I built a linear regression model using the number of lymph nodes as the response variable and the gender, operation year, and operation age as predictors. I am not sure how to interpret the results to answer my specific question. Should I be looking at the R squared? If so, is there a way to get a confidence interval for it? Thanks to anyone who can help. If you think I am going about this the wrong way, please let me know.
Call: lm(formula = LN_reviewed ~ Gender + Operation__year + Operation__age, data = sample_data) Residuals: Min 1Q Median 3Q Max -49.436 -15.280 -0.495 13.450 61.564 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -1.190e+04 1.459e+03 -8.159 9.95e-14 *** GenderMALE -5.542e+00 4.685e+00 -1.183 0.239 Operation__year 5.980e+00 7.296e-01 8.196 8.01e-14 *** Operation__age -2.524e-01 1.675e-01 -1.507 0.134 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 22.46 on 158 degrees of freedom Multiple R-squared: 0.2999, Adjusted R-squared: 0.2866 F-statistic: 22.56 on 3 and 158 DF, p-value: 3.268e-12