Statistician for nursing researchers: questionnaire validation (CFA, omega), reliability (alpha and omega), logistic regression and reviewer responses. PhD theses and Q1/Q2.
Statistics for nursing research that holds up to the committee and the reviewer
PhD theses, Q1/Q2 articles and scale validation in nursing: care, community health, management and education. Questionnaire validation with McDonald's omega, multilevel models, mixed methods and reviewer responses.
If your project fits any of these, there is method. The N of many nursing studies is perfectly workable.
You translated or adapted an instrument (quality of life, caregiver burden, self-efficacy, pain) and need full validation: EFA, CFA, omega, invariance and convergent validity.
Your data is not independent: patients within units, interventions within centers. You know you need multilevel models but the SPSS output is opaque.
Your thesis combines in-depth interviews with a validated questionnaire. The quantitative side must be solid and triangulated with the qualitative.
Exploratory and confirmatory factor analysis (lavaan), fit indices (CFI, RMSEA, SRMR), factor loadings and modification.
Total omega, hierarchical omega, Cronbach's alpha with 95% CI, ICC for continuous scales and kappa for agreement.
Patients nested in units or centers, fixed and random effects, level-2 ICC, longitudinal data handling.
Comparing your scale across men/women or countries: configural, metric and scalar invariance before comparing means.
Minimal important change (MIC), reliable change index (RCI), responders vs non-responders.
Triangulation, QUAN→QUAL or QUAL→QUAN sequences, methodological justification for demanding reviewers.
No clock running on your tab. We agree on scope, timeline and a fixed price upfront: no inflated hours, no surprise invoice at the end. Before delivery, every analysis goes through a careful review on my side: I rerun the code, re-check the assumptions and review tables and figures line by line. That's what I obsess over: that what you receive is ready to defend before your committee or reviewers without errors slipping through. If something out of scope appears, we discuss it before I touch it.
Illustrative example: McDonald's omega with 95% CI per subscale and the .70 threshold marked. This is the kind of figure (and its APA 7 table) you receive, ready for the Results section of your thesis or article.
Free material I use daily with nursing researchers. Start here before you write to me.
Questionnaire validation, multilevel models, mixed methods, reviewer response… Fill the form and I'll respond within 24h with a tentative proposal.
Biostatistics and statistical consulting for health research · All services
My expertise is quantitative. If your thesis is mixed methods, I cover the full quanti component and the methodological justification of the integration. For deep qualitative analysis I recommend a qualitative specialist: but triangulation and mixed reporting we do address together.
For classical EFA, N=80 is tight but defensible if the scale is short and items communicate well (subject/item ratio >5). For full CFA the ideal N is >150-200, but there are alternatives: SAM (Structural After Measurement), bootstrap, or CFA with loadings fixed to the exploratory solution. I'll tell you which fits your case.
Yes. It's one of the most requested services. I review the reviewer letter, run the additional analyses and help you draft the point-by-point response. Turnaround: 48-72h.
That's the priority. I don't deliver tables without explanation: every analysis comes with interpretation adapted to your level, plain language and examples of how to write up results. A Zoom session before defense is included if you want it.