produce a flextable describing a linear model produced by function lm.
You can remove significance stars by setting options options(show.signif.stars = FALSE).
lm model
unused argument
Other as_flextable methods: as_flextable(), as_flextable.data.frame(), as_flextable.gam(), as_flextable.glm(), as_flextable.grouped_data(), as_flextable.htest(), as_flextable.kmeans(), as_flextable.merMod(), as_flextable.pam(), as_flextable.summarizor(), as_flextable.table(), as_flextable.tabular(), as_flextable.tabulator(), as_flextable.xtable()
if (require("broom")) {
lmod <- lm(rating ~ complaints + privileges +
learning + raises + critical, data = attitude)
ft <- as_flextable(lmod)
ft
}
Estimate
Standard Error
t value
Pr(>|t|)
(Intercept)
11.011
11.704
0.941
0.3562
complaints
0.692
0.149
4.649
0.0001
***
privileges
-0.104
0.135
-0.769
0.4496
learning
0.249
0.160
1.560
0.1318
raises
-0.033
0.202
-0.165
0.8700
critical
0.015
0.147
0.105
0.9171
Signif. codes: 0 <= '***' < 0.001 < '**' < 0.01 < '*' < 0.05
Residual standard error: 7.139 on 24 degrees of freedom
Multiple R-squared: 0.7154, Adjusted R-squared: 0.6561
F-statistic: 12.06 on 24 and 5 DF, p-value: 0.0000
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