Expert quantitative support for researchers in psychology, education, social work, and social sciences — specialising in SEM, factor analysis, scale validation, and the full range of methods used in social science research.
We work with researchers across psychology and the social sciences — from Honours projects to postdoctoral publications.
We work with Honours, HDR and postdoctoral psychology researchers on the methods that define quantitative psychology research: structural equation modelling, confirmatory factor analysis, mediation and moderation analysis, and scale validation.
Statistical support for education researchers across school, vocational, and higher education contexts — including multilevel modelling for clustered data, ANCOVA for pre-post designs, and instrument development and validation.
We support social work, criminology, sociology, and community welfare researchers with the quantitative methods their studies require — including logistic regression, survival analysis, and psychometric scale validation.
We support the quantitative components of mixed-methods studies — including survey analysis, scale validation, and integration of quantitative findings with qualitative data.
The quantitative methods we specialise in for social science research:
Full-model SEM, path analysis, confirmatory factor analysis (CFA), and latent variable modelling.
Direct and indirect effects, PROCESS macro-equivalent analyses, and moderated mediation.
Exploratory factor analysis (EFA), CFA, Cronbach's alpha, McDonald's omega, convergent and discriminant validity, and measurement invariance testing.
Linear, logistic, hierarchical regression, and multilevel (HLM) models — for predictors of outcomes in survey and longitudinal data.
Independent and paired t-tests, ANOVA, MANOVA, ANCOVA, and non-parametric equivalents — with appropriate effect size reporting.
Repeated measures ANOVA, mixed models for longitudinal data, growth curve modelling, and pre-post intervention analysis.
Psychology and social science research increasingly demands methodological sophistication. Thesis committees and journal reviewers expect not just correct statistical tests but appropriate handling of construct validity, measurement error, and the complexity of human data.
SEM, CFA, and multilevel modelling are no longer advanced options — they are standard practice in high-quality psychology and education research. We help researchers apply these methods correctly, understand the outputs, and report them in ways that meet the expectations of examiners and peer reviewers.
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