REGRESSION ANALYSIS · METHOD GUIDE
One-on-one help choosing a regression model, checking the assumptions, reading the output, and reporting the results. You stay the author. You leave able to explain every coefficient to your committee.
Book a free consultation30 minutes · Bring your output, your plan, or your committee's comments.
WHERE YOU MIGHT BE STUCK
Most projects stall at one of three points.
Start with the one that fits.
Match the model to your outcome, your design, and your research question.
Odd signs, huge standard errors, and warnings usually have a diagnosable cause.
Turn output into accurate tables and wording you can defend.
DECISIONS THAT SHAPE YOUR ANALYSIS
Continuous outcomes usually call for linear regression, binary outcomes for logistic regression, counts for Poisson or negative binomial models, and ordered categories for ordinal models. Clustered or repeated data need a model that respects that structure.
Add variables because of the research question and the design, not because a longer list looks more thorough. A control can fix a problem or create one.
Residuals, influential cases, and multicollinearity checks show whether the estimates can be trusted. A failed check should change the plan, not just the footnote.
START ON YOUR OWN
Use these before or after your consultation.
Answer a few questions about your variables and design to find an appropriate test.
Choose a testFormat regression statistics correctly, with italics, spacing, and decimal places handled for you.
Format my resultsAn editable R Markdown workflow for continuous, count, ordinal, and binary outcomes.
See the workflowCorrelations, t tests, ANOVA, chi-square, and hierarchical regression with diagnostics.
See the workflowSeparate adjustment, sample changes, shared variation, and coding problems.
Read the CaseChoose adjustments for the question and design, not a longer variable list.
Read the CaseACADEMIC INTEGRITY
Dr. Yel does not write your dissertation or any chapter of it. The decisions, the interpretations, and the prose are yours. His role is to advise, teach, and review.
Nothing is handed over unexplained. We work through each method, assumption, and result until you can defend it on your own.
Programs differ in what outside help they allow. Check your policy and let your chair know you're working with a statistical consultant.
Dr. Yel declines work that would misrepresent authorship or data, such as writing chapters, altering or fabricating data, or anything your program's policy prohibits.
A FEW THINGS YOU MIGHT BE WONDERING
Yes. The measurement scale of your outcome and your research question decide the family of models, and we review your variables together before you commit to one.
It depends on which assumption fails and how badly. Options include a different model, robust standard errors, a justified transformation, or a sensitivity analysis. We go through the choices so you can explain the one you pick.
Analyses are run together in live sessions, with you watching or at the keyboard, so you can explain every step to your committee. You keep the syntax or code from every session.
R, SPSS, Stata, SAS, Mplus, and Python. We use whatever your program or committee expects.
Yes. We can review your tables, effect sizes, and wording for accuracy. You write the chapter.
The scope depends on your design, data, and the support you need. The free consultation is the place to discuss deliverables, pricing, and timing before you decide.
BRING THE MODEL THAT’S HOLDING YOU UP
Meet with Dr. Yel for a free 30-minute consultation about your study, data, or committee feedback.
Book a free consultationCan't find a time that works? Email bookingrequest@dissertationstatshelper.com with a few times you're available and your time zone, and we'll find a time. It's a new address, so if you don't see our reply, please check your spam folder.