total_scores.Rd
Calculate the total scores from sets of scores
total_scores(.data, ..., .method = "mean", .append = FALSE, .drop = FALSE)
.data | A data frame with columns to summed or averaged over. |
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... | A comma separated set of named tidy selectors, each of which selects a set of columns to which to apply the totalling function. |
.method | The method used to calculate the total. Must be one of "mean", "sum", or "sum_like". The "mean" is the arithmetic mean, skipping missing values. The "sum" is the sum, skipping missing values. The "sum_like" is the arithmetic mean, again skipping missing values, multiplied by the number of elements, including missing values. |
.append | logical If FALSE, just the totals be returned. If TRUE, the totals are appended as new columns to original data frame. |
.drop | logical If .append is TRUE, and if .drop is TRUE, then the variables being aggregated over are not returned. |
A new data frame with columns representing the total scores.
# Calculate the mean of all items beginning with `x_` and separately all items beginning with `y_` total_scores(test_psychometrics, x = starts_with('x_'), y = starts_with('y_')) #> # A tibble: 44 × 2 #> x y #> <dbl> <dbl> #> 1 2 2 #> 2 1.8 1.8 #> 3 2.1 2.8 #> 4 1.78 2.3 #> 5 1.1 1.6 #> 6 1.6 2.11 #> 7 2.5 3.2 #> 8 1.8 2.3 #> 9 1.5 2.2 #> 10 1.5 1.8 #> # … with 34 more rows # Calculate the sum of all items beginning with `z_` and separately all items beginning with `x_` total_scores(test_psychometrics, .method = 'sum', z = starts_with('z_'), x = starts_with('x_')) #> # A tibble: 44 × 2 #> z x #> <dbl> <dbl> #> 1 22 20 #> 2 17 18 #> 3 17 21 #> 4 30 16 #> 5 33 11 #> 6 27 16 #> 7 19 25 #> 8 17 18 #> 9 30 15 #> 10 23 15 #> # … with 34 more rows # Calculate the mean of all items from `x_1` to `y_10` total_scores(test_psychometrics, xy = x_1:y_10) #> # A tibble: 44 × 1 #> xy #> <dbl> #> 1 2 #> 2 1.8 #> 3 2.45 #> 4 2.05 #> 5 1.35 #> 6 1.84 #> 7 2.85 #> 8 2.05 #> 9 1.85 #> 10 1.65 #> # … with 34 more rows # Calculate the mean of all items beginning with `x_` and separately all items beginning with `y_`, # but append these means to the original, after have dropping the variables that # are aggregated over total_scores(test_psychometrics, x = starts_with('x_'), y = starts_with('y_'), .append = T, .drop = T) #> # A tibble: 44 × 12 #> z_1 z_2 z_3 z_4 z_5 z_6 z_7 z_8 z_9 z_10 x y #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 2 2 3 3 1 2 3 3 1 2 2 2 #> 2 1 1 1 2 1 2 2 2 4 1 1.8 1.8 #> 3 1 NA 2 2 3 2 2 1 2 2 2.1 2.8 #> 4 2 3 3 5 4 4 2 2 2 3 1.78 2.3 #> 5 4 4 4 3 3 3 3 5 3 1 1.1 1.6 #> 6 3 2 2 3 3 2 4 4 3 1 1.6 2.11 #> 7 2 2 1 1 2 2 1 3 2 3 2.5 3.2 #> 8 3 1 1 1 1 2 1 1 2 4 1.8 2.3 #> 9 2 3 3 3 3 3 4 2 4 3 1.5 2.2 #> 10 3 3 1 2 3 1 2 2 3 3 1.5 1.8 #> # … with 34 more rows