STATISTICAL METHODS
Statistical Methods
Consulting for Research
Our statistical methods consulting matches the analytical approach to your research question, study design, data structure and assumptions, from group comparisons and regression to survival analysis, evidence synthesis and qualitative analysis.
WHAT YOU WILL FIND
91 methods, from t-tests to thematic and meta-analysis
When each method applies, and what must hold
Run in SPSS, R, Stata or your software
WHAT YOU WILL FIND
91 methods, from t-tests to thematic and meta-analysis
When each method applies, and what must hold
Run in SPSS, R, Stata or your software
Statistical methods consulting is the selection, justification and application of the analytical approach that fits a study’s research question, design, outcome type and data structure, with results reported as estimates and their uncertainty. OnlineSPSS is a specialist statistical consultancy for academic, clinical and professional research, and the analysis is carried out in-house by PhD-level statisticians.
METHOD CATEGORIES
Statistical Methods for Research
We choose among statistical analysis methods by what the study needs to compare, estimate, explain, predict, model or synthesize, from core techniques to advanced statistical methods.
01
Comparative & Hypothesis Testing
For comparing groups, conditions and distributions
02
Regression & Predictive Modeling
For estimating relationships and predicting outcomes
03
Multivariate, Scale & Reliability
For analyzing multiple variables, scales and measurement structure
04
Structural & Latent Variable Modeling
For modeling latent constructs, pathways and complex relationships
05
Longitudinal & Multilevel Analysis
For repeated, nested, clustered and time-dependent data
06
Clinical, Survival & Epidemiological
For clinical outcomes, survival, diagnostic accuracy and population health
07
Evidence Synthesis & Meta-Research
For combining and evaluating evidence across studies
08
Bayesian & Computational Methods
For probabilistic estimation, resampling, simulation and missing data
09
Qualitative & Mixed Methods
For coding, interpretation and integrated qualitative-quantitative evidence
METHOD SELECTION
How We Choose the Right Statistical Method
Statistical method selection rests on six considerations about the study, settled before any model is fitted and never by a favorite test or a software menu.
Research Question Whether the aim is a difference, an association, a trajectory, a hazard or a pooled effect fixes the estimand, and the estimand narrows the model family.
Study Design Paired, clustered and repeated designs change which observations are independent, and randomization changes what a comparison can support causally, so an open design goes to Research Planning & Study Design first.
Outcome & Variable Type Binary, count, ordinal, continuous and time-to-event outcomes lead to different models, and how each predictor was measured matters as much as the outcome.
Data Structure & Assumptions Missingness, dependence, sparse categories and influential cases are judged through diagnostics and robustness checks, not a single pass-or-fail test.
Estimation Framework Likelihood-based, Bayesian and resampling approaches carry different assumptions and outputs, so the framework follows the prior information available, the model complexity and the conventions of the field.
Required Interpretation The reporting target, whether an adjusted effect, a prediction, a latent structure or a pooled estimate, decides how results are stated with effect sizes and intervals.
COMMON ANALYTICAL ISSUES
Where Statistical Method Selection Goes Wrong
Most failures begin before any test is run, which is why our Quantitative Data Analysis service starts from the design and the data structure.
Wrong Unit of Analysis Treating repeated measures, matched pairs or pupils within classrooms as independent misstates the standard errors: ignored clustering makes intervals look tighter than the data allow, and ignored pairing discards precision.
Missing Data Left to Defaults Silent listwise deletion can bias estimates and cost power. The missingness mechanism should be assessed and the chosen handling justified and reported.
Underpowered Models Too few observations for the effect of interest, or more parameters than the events can support, give imprecise and unstable estimates. Sample size belongs in the plan, not in a post hoc power calculation.
Choosing by Group Count or by Result Picking a test only from the number of groups, or switching models after seeing significance, answers the wrong question. Prespecify the primary analysis and label the rest exploratory.
P-Values Without Estimates A p-value alone hides the size and precision of an effect. Results need the effect estimate, its confidence interval and the diagnostics that support the model.
Causal Language Without a Causal Design Adjusted associations from observational data are not causal effects by default. Causal claims need a design, an explicit identification argument and a sensitivity analysis for unmeasured confounding.
SOFTWARE
Statistical Software
Each analysis is run in the software that fits the method and the project's reproducibility needs, with syntax or scripts provided where applicable.
RESEARCH DISCIPLINES
Statistical Methods Across Research Fields
Method choice also depends on each field's designs, data types and reporting conventions, from CONSORT and STROBE in clinical research to APA 7 in psychology and education.
RESEARCHER VOICE
What Researchers Say
Feedback from two research directors, on method strategy before further analysis and on support that adapts across several fields.
“We were at the point where several statistical approaches could have answered the project, and we needed a clear method strategy before doing more analysis. The team mapped the design, outcomes, assumptions, and reporting needs first, then showed us which methods genuinely fitted the research question. It saved us from doing a lot of unnecessary analysis.”
“Our team works across several research areas, so we needed statistical support that could adapt to very different study designs rather than apply the same template every time. The advice was consistently grounded in the field, the data structure, and the reporting standard expected for each project. That breadth was the main reason we kept coming back.”
FREQUENTLY ASKED QUESTIONS
Questions About Statistical Methods
Short answers to what researchers ask before sharing a project, from choosing a method to confidentiality, authorship and the assessment process.
Which statistical method should I use for my research?
The right statistical method follows from what the study must estimate and how the data were collected. We review the design and data first, so you do not need to know the method before contacting us. If a method has already been proposed, we confirm whether it fits or explain the alternative.
What information do you need to recommend an analytical approach?
To recommend an analytical approach, we need the research question, the study design, how outcomes and predictors were measured, and whether observations are independent, repeated or clustered. A protocol, analysis plan, reviewer comments or a description of the dataset is enough for an initial review. If an analysis has already been run and reviewers have questioned it, Independent Statistical Review is the service that examines it.
How do you protect my research data and confidentiality?
Research data and project details are handled confidentially, and project information is not published. An NDA is available where required and can be arranged before sensitive materials are shared. Read more about confidentiality and data security.
Is it appropriate to work with an external statistician on my research?
Yes. Statistical consulting is established professional practice in research. OnlineSPSS provides the agreed analytical support and claims no intellectual contribution. The research question, interpretation, conclusions and authorship remain with the researcher.
Can you advise on statistical methods before data collection begins?
Yes, and it is often the most useful time. Research methodology consulting at this stage can shape the primary outcome, sample size and power, and the statistical analysis plan, which is the scope of Research Planning & Study Design.
What happens when I request an assessment, and how long does it take?
You share your research question, design and relevant materials, and a statistically trained Research Coordinator reviews the request and responds the same day. The analytical work, deliverables, timeline and one fixed project fee are then confirmed before any work begins, so the timeline follows from the agreed scope rather than being quoted in advance.
Still have a question? Find more answers in our full FAQ.
NEXT STEP
Not Sure Which Statistical Method
Fits Your Research?
Share your research question, design and data. We review the requirements and identify an appropriate direction before any work begins.
No Commitment Required
Strictly Confidential
Fixed Project Fee
In-House PhD-Level Statisticians
Same-Day Response
Serving Researchers Since 2014