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Naive unadjusted indirect comparison

Source: R/naive.R
naive.Rd

Compute an unadjusted (naive) indirect treatment comparison by comparing crude outcomes from the IPD and AgD without any covariate adjustment. Returns treatment effect on the link scale plus absolute predictions (event probabilities, risk difference, risk ratio) for both populations.

Usage

naive(data, link = NULL, conf_level = 0.95)

Arguments

data

An mlumr_data object from combine_data()

Link function. For binomial: "logit" (default), "probit", or "cloglog". For normal/poisson: ignored (identity/log always used). If NULL, uses the canonical default.

conf_level

Confidence level for the interval (default 0.95)

Value

An object of class mlumr_naive

Details

For binomial outcomes, event-probability intervals use Wald standard errors and are bounded to [0, 1]. For Poisson outcomes, the log-rate contrast uses a 0.5 continuity correction when an observed event count is zero.

Examples

if (FALSE) { # \dontrun{
result <- naive(dat)
print(result)
} # }