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Research examples illustrating the service · Advanced example

Job autonomy, supervisor support and work engagement

A three-scale study with factor analysis, reliability, three hypotheses including regression, and an additional background-adjusted model.

360 participants · 3 scales · 3 hypotheses

The study at a glance

A cross-sectional observational study of hybrid and onsite employees in three tenure groups. The questionnaire contains 15 items, five for each of three scales. Work arrangement was not randomly assigned.

Research objective

Examine the questionnaire structure, the associations of autonomy and supervisor support with engagement, and engagement differences between work arrangements.

Research questions

  • Do the 15 items empirically distinguish autonomy, supervisor support and engagement?
  • How are autonomy and support associated with engagement separately and in a joint model?
  • Does mean engagement differ between hybrid and onsite employees?

Research hypotheses

  • H1: Job autonomy is positively associated with work engagement.
  • H2: Autonomy and supervisor support jointly predict engagement in a multiple linear regression compared with an intercept-only model.
  • H3: Mean engagement is higher in the hybrid group than in the onsite group.

What does the analysis include?

Examining the measurement structure

Exploratory factor analysis (EFA) of the 15 items, including suitability checks, factor-number assessment and oblique rotation. This preliminary measurement analysis is separate from the three research hypotheses. Scale scores are item means on a 1–5 scale.

  1. Sample, item and composite descriptives, with Cronbach alpha reliability for all three scales.
  2. H1: A Pearson correlation between autonomy and engagement.
  3. H2: Multiple regression with support and autonomy as predictors, including checks of residuals, variance, collinearity and influential observations.
  4. H3: A Welch test comparing mean engagement in two independent groups, with an effect size.
  5. Two-sided tests for the three hypotheses, with original p values and Holm-adjusted values for this family.

Additional analysis: background adjustment

Model A1 extends the regression with work arrangement and tenure groups. It is an explicitly defined exploratory analysis, evaluated separately from the three-hypothesis family. It examines associations after background adjustment; no model-improvement comparison is computed here.

What can the study tell us?

The observational associations and group differences cannot establish a causal effect of work arrangement. Factor analysis and reliability in one sample are not external validation. The expanded model requires cautious interpretation as an additional analysis.

Input files: where the analysis starts

Open the study brief, questionnaire, codebook and dataset to see the basis for the analysis. Each dataset row represents one participant.

Preparing your own file? Read the guide to preparing research data.

Outputs: what do you receive?

Explore each output or download the package. The documents describe the same study and analyses; the data and software outputs let you inspect the results and continue working with them.

Start with the findings chapter and explanation guide, then explore the underlying analysis outputs.

For the chapter structure and the distinction between findings and interpretation, read the guide to writing a results chapter.

Download the full output package (ZIP)

Consultation, analysis plan and itemized price

How variables and hypotheses were understood, which tests were selected, and the illustrative price breakdown.

Findings chapter

Research findings, tables and figures with statistical reporting for each hypothesis.

Methods section completion

Tests performed, scale scoring, data handling and assumption checks.

Relevant discussion guidance

Interpretation and limitations; connect the findings to your own research literature and sources.

Assumption check records

Structured check records. Readable explanations also appear in the methods, process report and software output.

How the work was done

Analysis decisions, completed steps and instructions for repeating the tests.

Quality check report

A checklist of output checks, including agreement between calculations and reporting.

Explanations and advisor meeting guide

Why each test was chosen, alternatives considered and how to explain the results.

Data and software output

SAV data, rerunnable syntax and SPSS-compatible output for detailed inspection.

Analysis data file

The data and scores used in the calculations, in CSV format.

Codebook

Variable names, meanings and coding for interpreting and reusing the files.

Charts and editable Excel workbooks

Findings and background charts with underlying chart data and editable workbooks.