Resource Library
Statistical analysis for psychology dissertation research.
A practical guide to psychology dissertation secondary data analysis, covering dataset appraisal, access, variable mapping, analytic samples, ethics, complex designs, reproducibility, and transparent reporting.
A practical guide to psychology dissertation structural equation modelling, covering latent variables, fit, power, invariance, estimation, and reporting.
A practical guide to psychology dissertation multilevel modelling, covering nested data, random effects, centring, power, diagnostics, and reporting.
A practical guide to psychology dissertation nonparametric tests, covering ranks, assumptions, effect sizes, exact methods, software, and reporting.
A practical guide to factor analysis in psychology dissertations, covering EFA, CFA, retention, rotation, item evaluation, model fit, and reporting.
A practical guide to normality testing in psychology dissertations, covering residuals, Q-Q plots, formal tests, robust alternatives, and reporting.
A practical guide to choosing, calculating, interpreting, and reporting effect sizes and confidence intervals in a psychology dissertation.
A practical guide to psychology dissertation outlier analysis, covering detection, influence, robust methods, sensitivity checks, and reporting.
A practical guide to psychology dissertation missing data, covering prevention, diagnosis, deletion, imputation, sensitivity analysis, and reporting.
A practical guide to psychology dissertation power analysis, covering effect sizes, sample-size inputs, sensitivity analysis, software, and reporting.
