Perform a Linear Regression within the Discordant Kinship Framework

discord_regression(
  data,
  outcome,
  predictors,
  id = "extended_id",
  sex = "sex",
  race = "race",
  pair_identifiers = c("_s1", "_s2")
)

Arguments

data	A data frame.
outcome	A character string containing the outcome variable of interest.
predictors	A character vector containing the column names for predicting the outcome.
id	A unique kinship pair identifier.
sex	A character string for the sex column name.
race	A character string for the race column name.
pair_identifiers	A character vector of length two that contains the variable identifier for each kinship pair.

Value

A tidy dataframe containing the model metrics via the tidy function.

Examples


discord_regression(data = sample_data,
outcome = "height",
predictors = "weight",
pair_identifiers = c("_s1", "_s2"),
sex = NULL,
race = NULL)
#> # A tibble: 4 x 5
#>   term        estimate std.error statistic  p.value
#>   <chr>          <dbl>     <dbl>     <dbl>    <dbl>
#> 1 (Intercept)   0.895    0.00638    140.   0.      
#> 2 height_mean   0.0809   0.00698     11.6  5.83e-31
#> 3 weight_diff   0.0506   0.00505     10.0  1.42e-23
#> 4 weight_mean  -0.0582   0.00764     -7.61 2.77e-14