Odds ratios are computed by exponentiating the estimated covariate effects on the logit-misclassification probabilities.
odds.msm(x, odds.scale = 1, cl = 0.95)Output from msm representing a fitted
multi-state model.
Vector with same elements as number of covariates on misclassification probabilities. Corresponds to the increase in each covariate used to calculate its odds ratio. Defaults to all 1.
Width of the symmetric confidence interval to present. Defaults to 0.95.
A list of tables containing odds ratio estimates, one table for each covariate. Each table has three columns, containing the odds ratio, and an approximate upper 95% and lower 95% confidence limit respectively (assuming normality on the log scale), for each misclassification probability.