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Create predicted y values from a data frame of x values.

Source: R/create_plot_data.R
create_y_estimates.Rd

Create predicted y values from a data frame of x values. There can be only exactly 2 columns of x values. The predicted y values can be estimated from an lm or glm model. Interaction terms are allowed, as are weights.

Usage

create_y_estimates(x_vals, model, coefficient_names)

Arguments

x_vals

A data frame or tibble with exactly two columns. The first column has x1 values and the second column has x2 values. These will form a curve or line if plotted in the regression surface. The column names do not matter.

model

A glm with exactly two x variables

coefficient_names

A named character vector that attaches coefficient names to standardized names (x1, x2, y)

Value

A data frame with x values and their corresponding predicted y values, as well as 95% confidence intervals

Examples

mymodel <- lm(r_shift ~ median_income16 + any_college, data = cali_counties)
xvars <- data.frame(x1 = seq(min(cali_counties$median_income16, na.rm=TRUE),
                             max(cali_counties$median_income16, na.rm=TRUE),
                              length.out=10),
                    x2 = seq(min(cali_counties$any_college, na.rm=TRUE),
                             max(cali_counties$any_college, na.rm=TRUE),
                             length.out=10))

predicted_xvars_data <- create_y_estimates(x_vals = xvars,
                                           model = mymodel,
                                           coefficient_names = c(y = "r_shift",
                                                                 x1= "median_income16",
                                                                 x2= "any_college") )