Adjust Raw Scores

Description

This function adjusts raw scores either by a fixed increment or according to a specified function. It can adjust scores stored in a list or within a specific column of a data frame.

Usage

adjust_raw_scores(df = NULL, raw, inc = 1)

Arguments

Value

If 'df' is NULL, the function returns a list containing the the adjusted raw scores. If 'df' is provided, the function returns a vector containing the adjusted raw scores.

Examples

# Create raw data
df <- data.frame(Id = 1:20,
RawScore = rep(11:15, 4))
# Increment scores by 2
df$AdjScore <- adjust_raw_scores(df, "RawScore", inc = 2)

# Adjust scores using a function
adjust_raw_scores(df = NULL, raw = list(11:15), inc = function(x) {x^2})

Interpreting Differences in Mean ACT Scores at the Composite Level

Description

The idmact_comp() function calculates and interprets differences in ACT composite scores. The function operates in the following steps:

1. Increment raw scores for one or more subjects for each student to obtain adjusted raw scores.

2. Map adjusted raw scores to adjusted scale scores using the form's raw score to scale score map.

3. Obtain each examinee's adjusted composite scale score by averaging the adjusted scale scores across subjects.

4. Calculate the adjusted and unadjusted mean composite scale scores across all observations.

5. Compute the difference between the adjusted and unadjusted mean composite scale scores.

Usage

idmact_comp(
  df = NULL,
  df_map = NULL,
  raw,
  inc,
  map_raw,
  map_scale,
  mcent_subj = function(x) mean(x, na.rm = TRUE),
  mcent_obs = function(x) round(sum(x)/length(x)),
  mcent_comp = function(x) mean(x, na.rm = TRUE),
  na.rm.max = TRUE
)

Arguments

Details

By default, the function parameters align with the method presented in Schiel (1998). However, you can specify arbitrary anonymous functions for different implementations.

Value

A list containing composite and subject level results. "composite_results" includes the difference between the adjusted and unadjusted mean composite scale scores (deltac), the mean adjusted and unadjusted composite scale scores (mscale), and a list of individual adjusted and unadjusted composite scale scores (scale). "subject_results" includes the outcomes from idmact_subj for each subject.

References

Schiel, J. C. (1998). Interpreting differences in ACT composite scores (ACT Research Report Series 98-1). ACT, Inc. URL: https://www.act.org/content/dam/act/unsecured/documents/ACT_RR98-01.pdf

Examples

# Example 1: Using df and df_map
df <- data.frame(raw1 = c(1, 2, 3), raw2 = c(1, 1, 1))
df_map <- data.frame(map_raw1 = c(1, 2, 3),
                     map_scale1 = c(20, 21, 22),
                     map_raw2 = c(1, 1, 1),
                     map_scale2 = c(20, 20, 20))
comp_mean <- idmact_comp(df = df,
                         df_map = df_map,
                         raw = c("raw1", "raw2"),
                         inc = 1,
                         map_raw = c("map_raw1", "map_raw2"),
                         map_scale = c("map_scale1", "map_scale2"))

# Example 2: Using lists
raw = list(list(1, 2, 3, 4, 5), list(1, 1, 1, 1, 1))
inc = list(1 , 1)
map_raw = list(list(1, 2, 3, 4, 5))
map_scale = list(list(20, 21, 22, 23, 24))
comp_mean <- idmact_comp(raw = raw,
                         inc = inc,
                         map_raw = map_raw,
                         map_scale = map_scale)

Interpret Differences in Mean ACT Scores at the Subject Level

Description

This function implements an algorithm to analyze differences in subject level scores.It first adjusts raw scores for each student, maps these adjusted raw scores to scale scores using the provided raw-to-scale score mapping (note: perfect raw scores are always converted to the maximum allowable scale score despite the adjustment in the previous step), then calculates the mean adjusted and unadjusted scale scores across all observations. The difference (delta) between these two mean scores is then computed. The adjustment and calculation method follows Schiel's (1998) methodology, but can also be customized with user-defined parameters and functions.

Usage

idmact_subj(
  df = NULL,
  df_map = NULL,
  raw,
  inc = 1,
  map_raw,
  map_scale,
  mcent_subj = function(x) mean(x, na.rm = TRUE),
  na.rm.max = TRUE
)

Arguments

Value

A list containing the following elements:

• 'deltas': the difference between the mean adjusted and unadjusted scale scores,

• 'm_scale': a list with the mean adjusted ('adj') and unadjusted ('unadj') scale scores,

• 'scale': a list with the individual adjusted ('adj') and unadjusted ('unadj') scale scores,

• 'raw': a list with the individual adjusted ('adj') and unadjusted ('unadj') raw scores.

References

Schiel, J. C. (1998). Interpreting differences in ACT composite scores (ACT Research Report Series 98-1). ACT, Inc. URL: https://www.act.org/content/dam/act/unsecured/documents/ACT_RR98-01.pdf

Examples

raw_scores = list(1, 2, 3, 4, 5)
map_raw_scores = list(1, 2, 3, 4, 5)
map_scale_scores = list(20, 21, 22, 23, 24)
idmact_subj(raw = raw_scores,
            map_raw = map_raw_scores,
            map_scale = map_scale_scores)

Elongate Mapping of Raw Scores to Scale Scores

Description

This function elongates the mapping of raw scores to scale scores. Each element in 'map_raw' and 'map_scale' is repeated according to the length of the corresponding 'map_raw' element, resulting in equal-length lists of map_raw' and 'map_scale' scores.

Usage

map_elongate(map_raw, map_scale)

Arguments

Value

A named list with two components: 'map_raw' and 'map_scale'. Each component is a list representing the elongated mapping of raw scores to scale scores.

Examples

# Elongate the mapping of raw scores (1:5 and 6:10) to scale scores (20 and 21)
map_elongate(map_raw = list(1:5, 6:10),
             map_scale = list(20, 21))

Elongate Data Frame Mapping of Raw Scores to Scale Scores

Description

This function takes a data frame that maps raw scores to scale scores, and elongates it. Each raw score range in the 'map_raw' column is split into individual scores, and each corresponding scale score in the 'map_scale' column is repeated for each individual raw score. The function returns a new data frame with each raw score paired with its corresponding scale score.

Usage

map_elongate_df(df_map, map_raw, map_scale)

Arguments

Value

An elongated data frame where each row represents a raw score and its corresponding scale score.

Examples

# Create a data frame mapping raw score ranges to scale scores
df_map <- data.frame(
 raw = c("1-5", "6-10"),
 scale = c(10, 11)
)
# Elongate the data frame
elongated_df <- map_elongate_df(df_map, "raw", "scale")
print(elongated_df)

Map Scores

Description

This function converts raw scores into scale scores using a provided mapping. The mapping can be provided directly as lists through 'map_raw' and 'map_scale', or indirectly via columns within either 'df' or 'df_map' data frames.

Usage

map_scores(
  df = NULL,
  df_map = NULL,
  conv,
  map_raw,
  map_scale,
  na.rm.max = TRUE
)

Arguments

Value

A list of scale scores.

Examples

# Convert raw scores to scale scores using lists
map_scores(conv = list(1, 2, 3, 4, 5),
           map_raw = list(1, 2, 3, 4, 5),
           map_scale = list(20, 21, 22, 23, 24))

# Convert raw scores to scale scores using a data frame
df <- data.frame(Id = 1:5, RawScore = 1:5)
df_map <- data.frame(Raw = 1:5, Scale = 20:24)
df$ScaleScore <- map_scores(df, df_map, conv = "RawScore", map_raw = "Raw", map_scale = "Scale")