ctSweepS: CTS–QCA: Single-condition threshold sweep

In TSQCA: Threshold Sweep Extensions for Qualitative Comparative Analysis

CTS–QCA: Single-condition threshold sweep

Description

Performs a threshold sweep for one focal condition X. For each threshold in sweep_range, the outcome Y and all X variables are binarized using user-specified thresholds, and a crisp-set QCA is executed.

Usage

ctSweepS(
  dat,
  outcome = NULL,
  conditions = NULL,
  sweep_var,
  sweep_range,
  thrY,
  thrX_default = 7,
  pre_calibrated = NULL,
  dir.exp = NULL,
  include = "",
  incl.cut = 0.8,
  n.cut = 1,
  pri.cut = 0,
  extract_mode = c("first", "all", "essential"),
  return_details = TRUE,
  Yvar = NULL,
  Xvars = NULL
)

Arguments

dat	Data frame containing the outcome and condition variables.
outcome	Character. Outcome variable name. Supports negation with tilde prefix (e.g., "~Y") following QCA package conventions.
conditions	Character vector. Names of condition variables.
sweep_var	Character. Name of the condition to be swept. Must be one of conditions.
sweep_range	Numeric vector. Candidate thresholds for sweep_var.
thrY	Numeric. Threshold for Y (fixed).
thrX_default	Numeric. Default threshold for non-swept X variables. Variables listed in pre_calibrated do not require this threshold.
pre_calibrated	Character vector or NULL. Names of condition variables that have been pre-calibrated (e.g., via QCA::calibrate()) and should be passed through to QCA::truthTable() without binarization. These variables must contain values in the [0, 1] range. Variables not listed here will be binarized using thrX_default as usual. Default is NULL (all variables binarized). It is recommended to sweep variables on their original (raw) scale rather than as pre-calibrated fuzzy values, because raw-scale thresholds are easier to interpret substantively.
dir.exp	Directional expectations for minimize. If NULL (default), no directional expectations are applied. To compute the intermediate solution, specify a numeric vector (1, 0, or -1 for each condition). Example: dir.exp = c(1, 1, 1) for three conditions all expected to contribute positively.
include	Inclusion rule for minimize. "" (default, QCA compatible) computes the complex solution without logical remainders. Use "?" to include logical remainders for parsimonious (with dir.exp = NULL) or intermediate solutions (with dir.exp specified).
incl.cut	Consistency cutoff for truthTable.
n.cut	Frequency cutoff for truthTable.
pri.cut	PRI cutoff for minimize.
extract_mode	Character. How to handle multiple solutions: "first" (default), "all", or "essential". See qca_extract for details.
return_details	Logical. If TRUE (default), returns both summary and detailed objects for use with generate_report().
Yvar	Deprecated. Use outcome instead.
Xvars	Deprecated. Use conditions instead.

Value

If return_details = FALSE, a data frame with columns:

• threshold — swept threshold for sweep_var

• expression — minimized solution expression

• inclS — solution consistency

• covS — solution coverage

• (additional columns depending on extract_mode)

If return_details = TRUE, a list with:

• summary — the data frame above

• details — per-threshold list of threshold, thrX_vec, truth_table, solution

Examples

# Load sample data
data(sample_data)

# === Three Types of QCA Solutions ===

# 1. Complex Solution (default, QCA compatible)
result_comp <- ctSweepS(
  dat = sample_data,
  outcome = "Y",
  conditions = c("X1", "X2", "X3"),
  sweep_var = "X3",
  sweep_range = 7,
  thrY = 7,
  thrX_default = 7
  # include = "" (default), dir.exp = NULL (default)
)
head(result_comp$summary)

# 2. Parsimonious Solution (include = "?")
result_pars <- ctSweepS(
  dat = sample_data,
  outcome = "Y",
  conditions = c("X1", "X2", "X3"),
  sweep_var = "X3",
  sweep_range = 7,
  thrY = 7,
  thrX_default = 7,
  include = "?"  # Include logical remainders
)
head(result_pars$summary)

# 3. Intermediate Solution (include = "?" + dir.exp)
result_int <- ctSweepS(
  dat = sample_data,
  outcome = "Y",
  conditions = c("X1", "X2", "X3"),
  sweep_var = "X3",
  sweep_range = 7,
  thrY = 7,
  thrX_default = 7,
  include = "?",
  dir.exp = c(1, 1, 1)  # All conditions expected positive
)
head(result_int$summary)

# === Threshold Sweep Example ===

# Run single condition threshold sweep on X3 (complex solutions by default)
result <- ctSweepS(
  dat = sample_data,
  outcome = "Y",
  conditions = c("X1", "X2", "X3"),
  sweep_var = "X3",
  sweep_range = 6:8,
  thrY = 7,
  thrX_default = 7
)
head(result$summary)

# Run with negated outcome (~Y)
result_neg <- ctSweepS(
  dat = sample_data,
  outcome = "~Y",
  conditions = c("X1", "X2", "X3"),
  sweep_var = "X3",
  sweep_range = 6:8,
  thrY = 7,
  thrX_default = 7
)
head(result_neg$summary)

TSQCA documentation built on Feb. 18, 2026, 5:06 p.m.