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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.
| 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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.