Fits a linear model of input dataframe

compute_lm_fit_df(data, xdata_col, ydata_col, conf_int = 0.95)

Arguments

data

A data frame containing C-QT analysis dataset

xdata_col

An unquoted column name for independent variable measurements

ydata_col

An unquoted column name for dependent variable measurements

conf_int

Numeric confidence interval level (default: 0.9)

Value

the fitted parameters of a lm of y ~ x

Examples

data_proc <- preprocess(cqtkit_data_verapamil)

compute_lm_fit_df(data_proc, RR, QT)
#> # A tibble: 1 × 9
#>   intercept slope intercept_ci_lower intercept_ci_upper slope_ci_lower
#>       <dbl> <dbl>              <dbl>              <dbl>          <dbl>
#> 1      280. 0.107               271.               289.         0.0974
#> # ℹ 4 more variables: slope_ci_upper <dbl>, p_value_intercept <dbl>,
#> #   p_value_slope <dbl>, conf_int <dbl>