Estimate MICs and Compare Groups
mic_solve.RdHigh‑level wrapper that returns:
delta_mic_results– additive pairwise differences (Δ‑MIC).ratio_mic_results– multiplicative pairwise ratios.dod_ratio_results– difference‑of‑differences on the ratio scale (ratio‑of‑ratios, a classic interaction on the log scale).dod_delta_results– difference‑of‑differences on the additive scale (Δ of Δs).
Usage
mic_solve(
clm_fit,
newdata = NULL,
conc_name,
transform_fun = log1p,
inv_transform_fun = expm1,
alpha = 0.05,
compare_pairs = "all",
pvalue_scale = c("lp", "logmic")
)Arguments
- clm_fit
Fitted object from
ordinal::clm().- newdata
Data frame with factor combinations to evaluate.
- conc_name
Character string giving the raw concentration column.
- transform_fun
Transformation used in the model (default
log1p).- inv_transform_fun
Inverse transformation (default
expm1).- alpha
Confidence‑level significance (default 0.05).
- compare_pairs
One of
"all"(default) to retain every pairwise comparison, or"share_any"to exclude contrasts where the two groups share no covariate levels innewdata.- pvalue_scale
Which pivot the main P_value uses for pairwise tests: "lp" (difference in lp = log1p(MIC), recommended for calibration) or "logmic" (current Wald on log(MIC) for ratios and MIC scale for deltas).
Examples
if (requireNamespace("ordinal", quietly = TRUE)) {
## Toy ordinal dataset
set.seed(1)
fit <- ordinal::clm(score ~ strain * treatment + log1p(conc), data = yeast_df)
res <- mic_solve(fit, conc_name = "conc")
head(res$ratio_mic_results)
}
#> Group1 Group2 Ratio_MIC log2Ratio_MIC SE_log2Ratio CI_Lower
#> 1 WT:None Mut:None 0.8344990 -0.2610177 0.1252559 -0.50651481
#> 2 WT:None WT:Salt 1.6783666 0.7470579 0.1062585 0.53879510
#> 3 WT:None Mut:Salt 0.9616983 -0.0563437 0.1174861 -0.28661220
#> 4 Mut:None WT:Salt 2.0112266 1.0080756 0.1176926 0.77740239
#> 5 Mut:None Mut:Salt 1.1524259 0.2046740 0.1277369 -0.04568565
#> 6 WT:Salt Mut:Salt 0.5729966 -0.8034016 0.1089813 -1.01700093
#> CI_Upper P_value
#> 1 -0.01552064 3.634335e-02
#> 2 0.95532068 1.564368e-12
#> 3 0.17392479 6.313981e-01
#> 4 1.23874884 1.903759e-18
#> 5 0.45503369 1.083454e-01
#> 6 -0.58980227 9.204372e-14