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RESEARCH SUPPORT

PhD Thesis Statistical Analysis
From Analysis Plan to Defensible Results

The analysis plan, the models and diagnostics, and the results tables for the empirical chapters of your doctoral thesis, carried out in-house by a PhD-level statistician on your data and explained so that you can defend every choice.

No Commitment Required

Strictly Confidential

In-House PhD-Level Statisticians

Fixed Project Fee

Same-Day Response

What Does Statistical Analysis for a PhD Thesis Involve?

PhD thesis statistical analysis turns a research question and a dataset into estimates, intervals and tests that an examiner can follow and challenge. It covers the choice of model, the preparation of the data, the diagnostics that show whether the model is defensible for your design, and the tables that report the results. OnlineSPSS, a specialist statistical consultancy for academic, clinical and professional research, provides this support to doctoral and PhD researchers: an in-house PhD-level statistician carries out the agreed analysis on your data and explains each decision in terms you can defend in a viva. The thesis, its argument and its conclusions remain yours.

WHEN TO ENGAGE

Four Points at Which Doctoral Researchers Seek Support

Doctoral researchers usually ask for statistical support at one of four points, and what the work involves differs at each: before data are collected, on a finished dataset, in drafting or after comments.

Analysis Plan Before Data The research questions are set and the data are not yet collected, so the design, the sample size reasoning and a prespecified analysis plan are agreed while they can still be changed.

Finished Dataset, Open Questions Data collection is complete and the models are not chosen, so the variable types, the missing data and the design are examined first and an analysis is proposed that fits them.

Output to Write Up Output exists, but the tables, the interpretation or the methods wording are not yet in a form an examiner will accept, and the results chapter needs estimates with their confidence intervals.

Examiner and Supervisor Comments A supervisor or examiner has questioned a model, an assumption or a reported test, and the analysis has to be re-examined against the design and answered with evidence.

WHAT THE SUPPORT COVERS

Statistical Components of a Doctoral Thesis We Support

Doctoral research statistics covers more than running tests, and these six components are what the support is built from, each agreed in the scope before work begins.

Analysis Plan

A thesis analysis plan ties each research question to an outcome, a model and its diagnostics, with the sample size reasoning, as part of Research Planning & Study Design.

Data Preparation

Coding, missing-data handling and the construction of variables are documented so that your supervisor can read them, and each decision to recode, exclude or impute is on record with its reason.

Analysis and Diagnostics

The agreed models are fitted on your data through Quantitative Data Analysis, with the diagnostics that show whether each model is defensible for your design.

Estimates and Intervals

Results are reported as effect estimates with confidence intervals and the sample behind them, with the p-value as one part of the evidence for each research question and not the whole of it.

Reporting the Statistics

Tables, figures and methods wording are prepared through Results Reporting & Interpretation, in the style your institution or target journal requires.

Review and Responses

Comments on the analysis are answered by re-examining it, and a completed analysis can be checked through Independent Statistical Review before submission.

COMMON THESIS ISSUES

Where Doctoral Statistical Analysis Goes Wrong

Most weaknesses that examiners find were built in before the output was produced, in the design, the plan or the handling of the data, and each of the checks below is made before a result is reported.

Test Chosen Before the Design A test is picked from a flowchart before anyone asks whether observations are independent, paired or clustered, and the examiner's first question is then about the design.

Power Considered Too Late Sample size is thought about after data collection, so a null result cannot be told apart from a study that was too small, and the interval has to carry the interpretation.

Many Tests, No Plan Several outcomes and subgroups are tested without a stated plan, which inflates the chance of false positives, so each analysis is labeled prespecified or exploratory and multiplicity is adjusted where appropriate.

Missing Data Dropped Silently Cases with missing values vanish from the analysis, which can bias estimates and shrink the sample, when the likely mechanism should be examined and the handling justified.

Assumptions Ticked Off One normality test is quoted as proof that a model fits, when assumptions are better judged from the design, the residuals and a check of how far the conclusions change without them.

Causal Wording From Association An association found in observational data is described with causal language in the discussion, which a careful examiner will challenge unless the design supports it.

DELIVERABLES

What You Receive for Your Thesis Analysis

The files and documents follow the scope agreed for your project, so that every number in the thesis can be traced to your data and explained to an examiner.

Analysis Plan Document A written plan linking each research question to its outcome, model, diagnostics and decision rules, which can be placed in your methods chapter or an appendix as you decide.

Cleaned Dataset and Codebook A cleaned dataset with a codebook of the recoding decisions, the missing-value codes used and the exclusions applied, each with the reason it was made.

Syntax and Output The syntax or scripts and the output behind every reported estimate, in the software your project uses, so that the analysis can be rerun from the data.

Results Tables and Figures Tables and figures prepared in the format your institution requires, with effect estimates, confidence intervals and the sample size behind each one.

Methods and Results Wording Statistical wording for the methods and results, matched to the output and to what the design supports, for you to check and incorporate.

Interpretation Notes Each estimate explained within the limits of the design, with its statistical limitations stated plainly.

ILLUSTRATIVE EXAMPLE

How a Thesis Analysis May Look in Practice

An illustration of how a doctoral comparison moves from an analysis plan to results that can be defended in an examination.

ILLUSTRATIVE EXAMPLE · REHABILITATION SCIENCE RESEARCH · UNITED STATES

A doctoral researcher in rehabilitation science wanted to compare functional recovery between patients who followed a home-based exercise program and patients who received usual care, with measurements at baseline and at three follow-up visits.

Group membership had not been randomized, so the analysis plan was written first: the primary outcome, the baseline covariates chosen from clinical reasoning, a linear mixed model for the repeated measurements and the handling of missed visits were all fixed before any group difference was inspected. The complication appeared at the first follow-up. Several participants had missed visits, and those who dropped out had started with poorer scores, so a complete-case analysis would have flattered both groups. The mixed model used every observed measurement under a stated assumption about the missing data, and a sensitivity analysis showed how far the conclusion depended on that assumption. The limits of a nonrandomized design were written into the interpretation.

Outcome: The researcher received the adjusted mean difference with its 95% confidence interval, the sensitivity analysis, the results tables, the written analysis plan, the syntax and statistical wording for the methods.

View Case Examples

This example does not describe a real client or project. We never share details of actual client work, in line with the confidentiality we promise every researcher. This illustrative example is included to show the type, scope, and standard of work involved in this kind of analysis.

SOFTWARE

Software Used for Thesis Analysis

The software follows your project, your supervisor's requirements and the model the design needs, and the analysis is carried out in the platform that fits, working from your files.

HOW WE ASSESS YOUR PROJECT

We Review Your Actual Research

Your assessment is based on a review of your actual research materials and analytical requirements, not a generic project category.

1

You Submit Your Project Details

Share whatever is available at the current stage, such as the research aim, protocol or proposal, dataset, variable list, manuscript or statistical requirements.

2

We Review Your Research and Define the Scope

Your statistically trained Research Coordinator reviews the materials to understand the study design, research questions, data structure, analytical requirements and expected deliverables. If clarification is needed, additional documents or information can be requested before the assessment is finalized.

ProposalAnalysis PlanDatasetCodebookExaminer Comments
3

Your Analysis Is Completed and Delivered

Once the scope and fixed project fee are agreed, the in-house statistician completes the work and the Research Coordinator remains the communication point through delivery, with the analysis, deliverables and timeline as agreed.

RESEARCH RESPONSIBILITY

Statistical Support Within Your Own Thesis

OnlineSPSS supports the statistical component of a doctoral project, and the research itself stays with the researcher, as each of the four points below makes explicit.

Agreed Statistical Support OnlineSPSS provides the agreed methodological, analytical and statistical reporting support, defined in a scope that is confirmed before any work begins.

No Intellectual Contribution OnlineSPSS does not claim any intellectual contribution to your thesis. Authorship remains the researcher's, from the first chapter to the last.

Your Research Decisions The research question, the literature review, the theoretical framing, the substantive interpretation, the discussion and the conclusions remain yours, with overall responsibility.

Confidential Handling Research data and project details are handled confidentially, project information is not published, and an NDA is available where required.

FREQUENTLY ASKED QUESTIONS

Questions About Statistical Support for a PhD Thesis

Short answers to what doctoral researchers ask before sharing a project, from what the support covers and where it stops to existing analyses, confidentiality and the assessment.

PhD statistical consulting at OnlineSPSS covers the statistical component of a doctoral thesis: the analysis plan, data preparation, the analysis with its diagnostics, and the reporting of results. It can begin before data collection or after examiner comments, and the scope is agreed in the assessment. The thesis itself, including its argument and conclusions, is yours.

No. OnlineSPSS supports the statistical component of the thesis: the analysis plan, the analysis, the tables and figures, and statistical wording for the methods and results, matched to the output, for you to check and incorporate. The literature review, the theoretical framing, the discussion and the conclusions are written by you, and OnlineSPSS claims no intellectual contribution, so authorship of the thesis remains yours.

Yes. A completed analysis can be re-examined against your design, its assumptions and the reporting expected in your field, with a statement of what stands and what should change. This suits a thesis in which a supervisor or examiner has questioned a model, and it applies whether the output came from menus, scripts or an AI tool. Any changes are agreed with you before they are made.

That is the purpose of the interpretation notes. Each choice, such as the model, the handling of missing data and the diagnostics, is documented in terms of your design, so that you can explain why it was made and what it shows. Statistical limitations are stated plainly, so that you do not meet them for the first time in an examination.

Your data and project details are handled confidentially, and project information is not published. Researcher names and institutions are not used publicly without permission. An NDA is available where required and can be arranged before sensitive materials are shared. Read more about confidentiality and data security.

You share your research question, design and relevant materials, such as a proposal, an analysis plan or a dataset, and a statistically trained Research Coordinator reviews the request and responds the same day. The analysis, deliverables, timeline and one fixed project fee are then confirmed before any work begins, so the timeline follows from the agreed scope.

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NEXT STEP

Discuss Your
Thesis Analysis With Us

Share your research questions, your design and the data you have, together with any comments from your supervisor or examiners. We review them and confirm the scope before any work begins.

No Commitment Required

Strictly Confidential

Fixed Project Fee

In-House PhD-Level Statisticians

Same-Day Response

Serving Researchers Since 2014