QuickPLS The method library
Methods in QuickPLS Pro
Choose an analysis by its research question. The guides give the settings, outputs and worked examples.
Not sure which method fits? Compare methods by research question.
PLS-SEM
Partial least squares structural equation modelling estimates relationships between constructs measured by several indicators. Use it to examine a measurement model and the paths specified by your research question.
fsQCA (Fuzzy-set Qualitative Comparative Analysis)
fsQCA studies how combinations of conditions relate to an outcome using calibrated set memberships.
CB-SEM and CFA
Covariance-based structural equation modelling tests a factor and path model against observed covariances. Confirmatory factor analysis focuses on the measurement part of that model.
NCA (Necessary Condition Analysis)
Necessary condition analysis examines whether an outcome is constrained by a minimum level of a condition.
Regression
Regression estimates how an observed outcome relates to one or more predictors. Choose the model according to the outcome and the research question.
PCA (Principal Component Analysis)
Principal component analysis summarises correlated numeric variables using a smaller set of components.
Consistent PLS (PLSc)
Consistent PLS adjusts estimates for measurement error when reflective indicators are intended to measure common factors.
Weighted PLS
Weighted PLS incorporates a case-weight variable when estimating a PLS model, so observations can contribute different amounts to the calculation.
GSCA (Generalized Structured Component Analysis)
GSCA estimates component scores and their relationships by fitting the measurement and structural parts of a model together.
PLS-SEM Bootstrapping
Estimate uncertainty for PLS model quantities by repeatedly sampling cases and fitting the model again.
PLSpredict and CVPAT
Assess predictions on held-out cases and compare predictive losses with a benchmark.
PLS Model Comparison
Compare the predictive performance of two PLS models on the same outcomes and held-out cases.
Prediction-Oriented Model Selection
Compare several candidate PLS specifications using a declared prediction and model-selection plan.
CB-SEM Model Comparison
Compare competing covariance-based models fitted to the same observed variables and cases.
CB-SEM Measurement Invariance
Measurement invariance examines whether a factor model measures the same concepts across groups.
CB-SEM Multigroup Analysis
Multigroup CB-SEM compares factor-model parameters between defined groups.
CB-SEM Moderator Analysis
Test whether an observed moderator changes a relationship between latent factors.
CB-SEM Product-Indicator Moderation
Product-indicator moderation estimates an interaction between two latent factors from products of their indicators.
GSCA Joint Relationships
GSCA Joint Relationships estimates component interactions and quadratic terms within a jointly fitted model.
Higher-order GSCA
Higher-order GSCA represents a broader concept through lower-order components and estimates its relationships with other constructs.
GSCA Adjusted Copulas
GSCA adjusted copulas adds diagnostic terms to score regressions when a predictor may be related to omitted influences.
CCA Composite Residual Diagnostics
Inspect the relationships left unexplained by a composite model.
PLS Exact-Fit Assessment
Assess whether the model’s measurement and structural restrictions reproduce the observed relationships.
PLSc Exact-Fit Assessment
Assess whether the model’s measurement and structural restrictions reproduce the observed relationships.
Confirmatory Tetrad Analysis
Test covariance restrictions implied by a reflective measurement model.
Importance-Performance Map Analysis (IPMA)
Compare a construct’s total relationship with a target outcome against its average performance.
Gaussian-Copula Endogeneity Diagnostics
Investigate whether a questioned predictor may be associated with the error in a structural equation.
Quadratic Nonlinear Effects
Estimate a curved relationship and examine how its slope changes across observed values.
Blindfolding (Q²)
Blindfolding assesses omission-based predictive relevance within an estimated model.
HTMT and HTMT+ Discriminant Validity
Assess whether reflective constructs are sufficiently distinct from one another.
Global Goodness of Fit (GoF)
Calculate the historical PLS global GoF index and understand what it summarises.
PLSc Consistent Bootstrapping
Estimate uncertainty by repeating both the PLS fit and its consistent correction in each bootstrap sample.
PLSc Consistent Permutation
Compare group relationships by permuting group membership and refitting the consistent PLS model.
Structural Path Randomization
Test selected structural relationships using the stated randomization procedure on fixed PLS scores.
Post-hoc Technical Minimum Sample Size
Calculate a retrospective sample-size diagnostic from the fitted PLS model and its linked inference.
PLS-SEM Sample Size and Power
Plan a supported PLS study by simulating data at candidate sample sizes under explicit assumptions.
MICOM and Multigroup Analysis
Check whether composites are comparable across groups, then test differences in their structural relationships.
FIMIX-PLS
Explore whether a mixture of latent segments describes different structural relationships in the sample.
PLS-POS
Explore segments whose PLS structural relationships differ using a prediction-oriented partitioning procedure.
PLS-SEM Conditional Process Analysis
Study indirect relationships that depend on the value of a moderator.
Interventional Mediation
Estimate outcome contrasts under a specified treatment change and intervention on a mediator distribution.
Mediation and Moderation
Mediation concerns an indirect pathway; moderation concerns a relationship that changes with another variable.
fsQCA Studies and Specifications
Keep the data, set definitions and analysis choices for an fsQCA study together.
fsQCA Truth Tables
A truth table groups cases by configurations and shows how each configuration relates to the outcome.
fsQCA Solutions and Case Interpretation
Connect each solution pathway to the cases it covers and to the assumptions used to obtain it.
fsQCA Outcome Presence and Absence
Analyse an outcome and its absence as two separate set relationships.
fsQCA Robustness Analysis
Examine how conclusions change under defensible alternatives to the original fsQCA choices.
fsQCA Research Reports
Prepare an fsQCA report that connects the research question, analysis choices, solutions and cases.
fsQCA Counterfactual Reasoning
Understand which unobserved configurations are used to simplify a solution.
Compound Necessity in fsQCA
Assess whether an outcome requires a defined combination of conditions.
Advanced fsQCA Calibration
Translate measured values into set memberships using an explicit substantive definition.
Multi-value QCA (mvQCA)
Use categorical conditions whose named states cannot be reduced meaningfully to presence or absence.
Temporal QCA
Represent timing or sequences explicitly before examining configurational relationships.
Panel Set-fit Diagnostics
Compare set relationships across units and periods in panel data.
fsQCA Multiple Outcomes
Organise comparable set analyses for several explicitly defined outcomes.
Coincidence Analysis (CNA)
Search for configurational dependencies that may connect one or several outcomes.
Exact Binomial Checks for QCA
Assess a crisp truth-table row against an explicit null success probability.
Expanded fsQCA
Run a larger configurational study while keeping search size, thresholds and solution alternatives explicit.
Looking for an example from published research? Browse the paper tutorials.