summary_c2c | R Documentation |

adjusting lm object results according to original number of degree of freedom. The standard errors, t statistics and p values have to be adjusted because of replicated observations.

summary_c2c(x, df_old, df_new = x$df.residual)

`x` |
lm object |

`df_old` |
integer number of d.f in original dataset. For bigger datasets 'nrow' should be sufficient. |

`df_new` |
integer number of d.f in dataset with replicated rows, Default: x$df.residual |

The size of the correction is equal to sqrt(df_new / df_old).
Where standard errors are multiplied and t statistics divided by it.
In most cases the default `df_new`

value should be used.

data.frame with additional columns over a regular summary.lm output, like correct and statistics adjusted by it.

data("occup_small", package = "cat2cat") data("trans", package = "cat2cat") occup_old <- occup_small[occup_small$year == 2008, ] occup_new <- occup_small[occup_small$year == 2010, ] occup_2 <- cat2cat( data = list( old = occup_old, new = occup_new, cat_var = "code", time_var = "year" ), mappings = list(trans = trans, direction = "backward"), ml = list( data = occup_new, cat_var = "code", method = "knn", features = c("age", "sex", "edu", "exp", "parttime", "salary"), args = list(k = 10) ) ) # Regression # we have to adjust size of std as we artificialy enlarge degrees of freedom lms <- lm( formula = I(log(salary)) ~ age + sex + factor(edu) + parttime + exp, data = occup_2$old, weights = multiplier * wei_freq_c2c ) summary_c2c(lms, df_old = nrow(occup_old))

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.