Tables of model estimates

First, we load the package and estimate some regression models.

library(memisc)
lm0 <- lm(sr ~ pop15 + pop75,              data = LifeCycleSavings)
lm1 <- lm(sr ~                 dpi + ddpi, data = LifeCycleSavings)
lm2 <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)

Next, we put them together into a table with mtable().

mtable123 <- mtable("Model 1"=lm0,"Model 2"=lm1,"Model 3"=lm2,
                    summary.stats=c("sigma","R-squared","F","p","N"))

Third, we improve the appearance of the results by relabeling the mtable object.

mtable123 <- relabel(mtable123,
                      "(Intercept)" = "Constant",
                      pop15 = "Percentage of population under 15",
                      pop75 = "Percentage of population over 75",
                      dpi = "Real per-capita disposable income",
                      ddpi = "Growth rate of real per-capita disp. income"
)

Finally we view the results in HTML format.

show_html(mtable123)

	Model 1			Model 2			Model 3
Constant	30	.	628***	6	.	360***	28	.	566***
	(7	.	409)	(1	.	252)	(7	.	355)
Percentage of population under 15	−0	.	471**				−0	.	461**
	(0	.	147)				(0	.	145)
Percentage of population over 75	−1	.	934				−1	.	691
	(1	.	041)				(1	.	084)
Real per-capita disposable income				0	.	001	−0	.	000
				(0	.	001)	(0	.	001)
Growth rate of real per-capita disp. income				0	.	529*	0	.	410*
				(0	.	210)	(0	.	196)
R-squared	0	.	262	0	.	162	0	.	338
sigma	3	.	931	4	.	189	3	.	803
F	8	.	332	4	.	528	5	.	756
p	0	.	001	0	.	016	0	.	001
N	50			50			50
Significance: * = p < 0.001; = p < 0.01; * = p < 0.05

The results can be written into an HTML file using write_html(mtable123,file="mtable123.html") or the like. MS Word or LibreOffice can import such a file.