Generate a forest plot with a table, optimized for logistic regression.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | gg_glmforest(
glm_list,
stats.predictor_var,
stats.conf_interval = 0.95,
stats.effect_sig_digits = 3,
stats.sig_pvalue = waiver(),
label.effect_size = paste("OR per unit", stats.predictor_var),
label.dependent_var = "Dependent Var.",
plot.rel_width = 0.33,
plot.point.size = 1.8,
plot.point.color = "dodgerblue4",
plot.row.color = adjustcolor(plot.point.color, alpha.f = 0.04),
plot.breaks = waiver(),
plot.vertical.pos = waiver(),
plot.vertical.label = waiver()
)
|
glm_list |
A named list of the results of calls to |
stats.predictor_var |
The name of the variable in the linear model that is being regressed on (i.e., the predictor variable). |
stats.conf_interval |
Confidence interval. Default = 95%. |
stats.effect_sig_digits |
Number of significant figures to for effect size and confidence interval |
stats.sig_pvalue |
(Not used) significant p-value after correction for multiple comparisons. |
label.effect_size |
Label/column header describing the effect size. |
label.dependent_var |
Label/column header for the dependent variables (i.e., predicted variables). |
plot.rel_width |
Width of the forest plot relative to the width of the table. Default = 0.33. |
plot.point.size |
Size of the boxes in the forest plot. Default = 1.8. |
plot.point.color |
Color of the boxes in the forest plot. Default = "dodgerblue4". |
plot.row.color |
Background color of alternating rows of the table. Default = "dodgerblue4" with 4% transparency. Use NA to omit background colors. |
plot.breaks |
Breaks to use on the horizontal axis of the forest plot. |
plot.vertical.pos |
Vertical position of the indicator line on the forest plot. Default = 1 for logistic regression, 0 otherwise. Use NA to omit. |
plot.vertical.label |
Boolean, whether to add a label on the horizontal axis corresponding to the vertical indicator, if not already included in the breaks. |
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