do_steps: Calculate Steps for Uneven Data Points

In dropR: Dropout Analysis by Condition

Calculate Steps for Uneven Data Points

Description

The do_steps function calculates steps for data points represented by numbers of questions from the original experimental or survey data in x and remaining percent of participants in y.

Usage

do_steps(x, y, return_df = TRUE)

Arguments

x	Numeric vector representing the question numbers
y	Numeric vector representing the remaining percent of participants
return_df	Logical. If TRUE, the function returns a data frame; otherwise, it returns a list.

Details

Due to the nature of dropout/ survival data, step functions are necessary to accurately depict participants remaining. Dropout data includes the time until the event (a.k.a. dropout at a certain question or time), so that changes in remaining participants are discrete rather than continuous. This means that changes in survival probability occur at specific points and are better represented as steps than as a continuum.

Value

Returns a data frame or a list containing the modified x and y values.

Examples

x <- c(1, 2, 3, 4, 5)
y <- c(100, 100, 95, 90, 85)
do_steps(x, y)

# Using the example dataset dropRdemo

do_stats <- compute_stats(df = add_dropout_idx(dropRdemo, 3:54),
by_cond = "experimental_condition",
no_of_vars = 52)

tot_stats <- do_stats[do_stats$condition == "total", ]
do_steps(tot_stats$q_idx, tot_stats$pct_remain)

dropR documentation built on July 3, 2024, 5:06 p.m.