Type:	Package
Title:	Descriptive, Reliability, and Inferential Tables for Psychometric Scales and Demographic Data
Version:	0.2.0
Description:	Provides functions to format and summarise already computed outputs from commonly used statistical and psychometric functions into compact, single-row tables and simple graphs, with utilities to export results to CSV, Word, and Excel formats. The package does not implement new statistical methods or estimation procedures; instead, it organises and presents results obtained from existing functions such as psych::describe(), psych::alpha(), stats::t.test(), and gtsummary::tbl_summary() to streamline reporting workflows in clinical and psychological research.
License:	MIT + file LICENSE
Encoding:	UTF-8
RoxygenNote:	7.3.3
Imports:	dplyr, gtsummary, purrr, rlang, stats, officer, openxlsx, utils, psych
Suggests:	testthat (≥ 3.0.0)
Config/testthat/edition:	3
NeedsCompilation:	no
Packaged:	2026-02-11 07:41:57 UTC; HP
Author:	Darshankumar Dharaiya [aut, cre]
Maintainer:	Darshankumar Dharaiya <dharaiya.darshan@gmail.com>
Depends:	R (≥ 4.1.0)
Repository:	CRAN
Date/Publication:	2026-02-11 10:20:02 UTC

Wrap a pre computed psych::alpha object into a single row table

Description

Wrap a pre computed psych::alpha object into a single row table

Usage

make_alpha_table(alpha_res, scale_name = "Scale")

Arguments

Value

A data frame with columns: Scale, 95% CI lower, Alpha, 95% CI upper

Examples

# Create a minimal "psych::alpha" like object manually
alpha_obj <- list(
  total = list(
    raw_alpha = 0.85,
    lower = 0.78,
    upper = 0.92
  )
)

# Generate the formatted alpha table
make_alpha_table(alpha_obj, scale_name = "PHQ-9")

Create a one-row summary table for a chi-square test

Description

This function formats the result of a pre-computed chisq.test() into a single-row, report-ready data frame. It supports goodness-of-fit, independence, and homogeneity chi-square tests and includes an appropriate effect size with a qualitative interpretation.

Usage

make_chisq_test_table(
  chisq_object,
  test_type = c("goodness-of-fit", "independence", "homogeneity")
)

Arguments

Details

The function does not perform the chi-square test itself and does not introduce new statistical methods. All test statistics are extracted directly from the supplied chisq.test() object.

For goodness-of-fit tests, Cohen’s w is reported. For tests of independence and homogeneity, Cramér’s V is reported. Effect size interpretations follow conventional benchmarks (0.10 = small, 0.30 = medium, 0.50 = large).

Value

A single-row data frame with the following columns:

• test: Type of chi-square test

• chi_square: Chi-square statistic

• df: Degrees of freedom

• p_value: p-value

• N: Total sample size

• effect_size: Effect size (Cohen’s w or Cramér’s V)

• effect_type: Type of effect size reported

• effect_interpretation: Qualitative interpretation of effect size

Examples

# Goodness-of-fit example
observed <- c(40, 30, 50)
chisq_gof <- chisq.test(observed)

make_chisq_test_table(
  chisq_object = chisq_gof,
  test_type = "goodness-of-fit"
)

# Independence test example
tbl <- matrix(c(20, 30, 10, 40), nrow = 2)
chisq_ind <- chisq.test(tbl)

make_chisq_test_table(
  chisq_object = chisq_ind,
  test_type = "independence"
)

Export a data frame to CSV, Word, or Excel

Description

This function exports a data frame as a structured table to a file in CSV, Word (.docx), or Excel (.xlsx) format.

Usage

make_dataframe_to_output(x, filename = NULL, format = "csv", path = NULL)

Arguments

Details

If no output path is specified, the file is written to a temporary directory using tempdir(). For reproducible workflows, users are encouraged to explicitly specify an output location, either the current working directory or a full file path.

• CSV files are written using utils::write.csv()

• Word (docx) files are created using the officer package

• Excel (xlsx) files are created using the openxlsx package

Value

Invisibly returns the full file path to the generated output file.

Examples

## Not run: 
df <- data.frame(x = 1:3, y = c("A", "B", "C"))

# 1. Default behaviour: write to a temporary directory (CRAN-safe)
make_dataframe_to_output(df, format = "csv")

# 2. Write to the current working directory (recommended for projects)
make_dataframe_to_output(
  df,
  format = "csv",
  path = "getwd"
)

# 3. Write to a user-specified directory
make_dataframe_to_output(
  df,
  filename = "demo_table",
  format = "excel",
  path = tempdir()
)

## End(Not run)

Create a demographics summary table

Description

Create a demographics summary table

Usage

make_demographic_table(data, vars, continuous_vars = NULL)

Arguments

Value

A gtsummary table

Examples

# Minimal example data
df <- data.frame(
  age = c(25, 30, 35),
  sex = c("M", "F", "M"),
  education = c("HS", "BA", "MA")
)

# Generate a demographic summary table (assign to object to avoid printing)
demo_table <- make_demographic_table(df, vars = c("age", "sex", "education"))
demo_table # optionally inspect the table

Create a one-row summary table for an independent-samples t-test

Description

This function performs an independent-samples t-test (Welch's t-test by default) between two groups defined by a binary grouping variable and returns a single-row, report-ready data frame. The output includes group names, sample sizes, mean difference, test statistics, p-value, and effect size (Cohen's d) with a qualitative interpretation.

Usage

make_independent_t_test_table(data, outcome, group)

Arguments

Details

The function is intended for streamlined reporting and does not introduce new statistical methods. All computations rely on stats::t.test().

Welch’s t-test is used by default, which does not assume equal variances. Cohen’s d is computed using the pooled standard deviation for comparability with conventional benchmarks. Group ordering follows the factor level order of the grouping variable.

Value

A single-row data frame with the following columns:

• test: Name of the statistical test

• group1, group2: Group labels

• mean_diff: Mean difference between groups (group1 - group2)

• t_value: t statistic

• df: Degrees of freedom

• p_value: p-value

• n_group1, n_group2: Sample sizes per group

• cohens_d: Cohen's d effect size

• interpretation: Qualitative interpretation of effect size

Examples

set.seed(123)

data_t <- data.frame(
  group = rep(c("CBT", "Psychodynamic"), each = 30),
  score = c(
    rnorm(30, mean = 18, sd = 4),
    rnorm(30, mean = 21, sd = 4)
  )
)

make_independent_t_test_table(
  data = data_t,
  outcome = "score",
  group = "group"
)

Create a one-row summary table of a paired t-test

Description

This function performs a paired t-test between two numeric variables in a data frame and returns a one-row summary table including means, mean difference, t-value, degrees of freedom, p-value, and confidence interval.

Usage

make_paired_t_test_table(
  data,
  var1,
  var2,
  var_name = NULL,
  alternative = "two.sided",
  conf.level = 0.95
)

Arguments

Value

A one-row data frame with columns:

• Variable - variable name

• Mean_obs1 - mean of observation 1

• Mean_obs2 - mean of observation 2

• Mean_diff - mean difference (obs1 - obs2)

• t_value - t statistic

• df - degrees of freedom

• p_value - p-value

• CI_lower - lower bound of confidence interval

• CI_upper - upper bound of confidence interval

Examples

# example data
df <- data.frame(
  before = c(10, 12, 14, 15, 11),
  after  = c(11, 13, 13, 16, 12)
)

# Run the paired t-test summary
make_paired_t_test_table(df, var1 = "before", var2 = "after")

Create a Descriptive Statistics Table Row

Description

Computes and formats descriptive statistics for a scale total score into a single-row data frame suitable for reporting.

Usage

make_scale_description_table(x, scale_name, type = NULL)

Arguments

Details

This function is intended for reporting descriptive statistics of total scale scores, for which descriptive statistics are computed internally using psych::describe() or base::summary().

Value

A single-row data frame with formatted descriptive statistics.

Examples

{
  phq9_data <- as.data.frame(matrix(sample(0:3, 10 * 9, replace = TRUE), 10, 9))
  colnames(phq9_data) <- paste0("Q", 1:9)
  phq9_data$total <- rowSums(phq9_data)

  make_scale_description_table(phq9_data$total, scale_name = "PHQ-9")
}

scaledescr

Description

Provides helper functions to format and summarise already computed outputs from commonly used statistical and psychometric functions into compact, single-row tables and simple graphs. Functions such as make_scale_description_table(), make_demographic_table(), make_alpha_table(), make_paired_t_test_table(), and make_dataframe_to_output() organise results obtained from existing functions including psych::describe(), psych::alpha(), stats::t.test(), and gtsummary::tbl_summary() for streamlined reporting and export to CSV, Word, and Excel formats. The package does not implement new statistical methods or perform additional estimation.