Maximum likelihood estimates with CIs of the grouping and strata effects

Described in Chapter 10 "Stratified 2x2 Tables and Meta-Analysis"

ML_estimates_and_CIs_stratified_2x2(n, link = "log", alpha = 0.05)

Arguments

n: the observed table (a 2x2xk matrix, where k is the number of strata)
link: the link function ('linear', 'log', or 'logit')
alpha: the nominal level, e.g. 0.05 for 95% CIs

Value

An object of the contingencytables_result class, basically a subclass of base::list(). Use the utils::str() function to see the specific elements returned.

Examples

# Smoking and lung cancer (Doll and Hill, 1950)
ML_estimates_and_CIs_stratified_2x2(doll_hill_1950)
#> Maximum likelihood estimates:
#>   alphahat   = -1.4619 (95% CI -1.8468 to -1.0771)
#>   betahat    =  0.7836 (95% CI 0.4000 to 1.1672)
#>   gammahat_2 =  0.2122 (95% CI 0.0276 to 0.3967)

# Prophylactice use of Lidocaine in myocardial infarction (Hine et al., 1989)
ML_estimates_and_CIs_stratified_2x2(hine_1989)
#> Maximum likelihood estimates:
#>   alphahat   = -3.6038 (95% CI -4.7575 to -2.4500)
#>   betahat    =  0.5461 (95% CI 0.0247 to 1.0676)
#>   gammahat_2 =  0.8890 (95% CI -0.4014 to 2.1793)
#>   gammahat_3 =  0.2196 (95% CI -1.0428 to 1.4820)
#>   gammahat_4 =  0.4598 (95% CI -0.7767 to 1.6962)
#>   gammahat_5 =  0.2177 (95% CI -1.0444 to 1.4799)
#>   gammahat_6 =  0.2935 (95% CI -0.9191 to 1.5061)