Reliability and Validity in Research Explained (2026 Guide)
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Shruti Sharma
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Reliability and validity are the two fundamental pillars of research quality. They determine whether your findings can be trusted, whether your measures are accurate, and whether your conclusions are justified. In a PhD viva, examiners will almost certainly probe your understanding of and strategies for ensuring both.
Reliability vs Validity: Core Definitions
Reliability vs Validity
If the study were repeated, would the same results be obtained? Can the findings be trusted to be stable and consistent?
Does the study actually measure what it claims to measure? Are the findings credible and true?
An analogy: A weighing scale that consistently shows you as 5kg heavier than you are is reliable (consistent) but not valid (inaccurate). A scale that gives random readings is neither reliable nor valid.
Types of Validity in Research
| Type of Validity | Definition | How to Establish |
|---|---|---|
| Content Validity | The measure covers all relevant aspects of the construct | Expert review of instrument items; systematic item development from theory |
| Face Validity | The measure appears to measure what it claims | Expert or participant review of face relevance |
| Construct Validity | The measure accurately represents the underlying theoretical construct | Confirmatory factor analysis, convergent and discriminant validity |
| Criterion Validity | The measure correlates with an established criterion | Concurrent validity (at the same time) or predictive validity (future criterion) |
| Internal Validity | The study controls for confounding factors; causal claims are justified | Randomisation, control groups, controlling extraneous variables |
| External Validity | Findings can be generalised to other populations or settings | Random sampling, representative sample, replication |
Types of Reliability in Research
| Type of Reliability | Definition | Measurement |
|---|---|---|
| Internal Consistency | Items within a scale measure the same construct consistently | Cronbach's alpha (α ≥ 0.70 acceptable) |
| Test-Retest Reliability | Same instrument gives consistent results over time | Correlation coefficient between two administrations |
| Inter-Rater Reliability | Different observers/coders give consistent ratings | Cohen's kappa, percentage agreement |
| Parallel Forms Reliability | Two equivalent versions of a test give consistent results | Correlation between two test forms |
| Split-Half Reliability | Two halves of a scale give consistent results | Spearman-Brown coefficient |
Validity and Reliability in Qualitative Research
The traditional concepts of validity and reliability apply to quantitative research. In qualitative research, the parallel framework is trustworthiness (Lincoln & Guba, 1985), which includes four criteria:
| Trustworthiness Criterion | Quantitative Parallel | Strategies |
|---|---|---|
| Credibility | Internal validity | Member checking, prolonged engagement, triangulation, peer debriefing |
| Transferability | External validity | Thick description, purposive sampling, detailed context reporting |
| Dependability | Reliability | Audit trail, methodology documentation, overlap methods |
| Confirmability | Objectivity | Reflexivity, audit trail, negative case analysis |
Threats to Internal Validity
In experimental and quasi-experimental research, internal validity can be threatened by:
- History — Events outside the study affect outcomes
- Maturation — Participants change over time naturally
- Selection bias — Differences between groups before the study begins
- Mortality/Attrition — Participants dropping out differentially between groups
- Testing effects — Familiarity with a test from prior exposure
- Instrument decay — Changes in measurement instruments over time
Strategies for Ensuring Validity and Reliability
- Pilot test your instruments before full data collection
- Use validated scales from existing published research where possible
- Triangulate — use multiple methods, data sources, or analysts
- Member checking — share findings with participants for verification (qualitative)
- Calculate Cronbach's alpha for all scales in quantitative studies
- Maintain an audit trail — document all decisions throughout the research process
- Practice reflexivity — acknowledge and manage your own bias and positionality
PhD Viva Tip
Examiners will almost always ask: 'How did you ensure the validity of your findings?' Prepare a specific, detailed answer covering the strategies you used. For quantitative studies, report Cronbach's alpha values and validity testing results. For qualitative studies, describe specific trustworthiness strategies you implemented throughout your study.
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Frequently Asked Questions
Click a question to expand the answer.
Validity refers to whether a study measures what it claims to measure — are the findings accurate and credible? Reliability refers to consistency — if the study were repeated, would the same results be obtained? A study can be reliable (consistently measuring the same thing) but not valid (if it's measuring the wrong thing). Both are needed for credible research.
The main types of validity are: (1) Content validity — does the measure cover all aspects of the construct? (2) Construct validity — does the measure accurately represent the theoretical construct? (3) Criterion validity — does the measure correlate with other established measures? (4) Internal validity — are the study's conclusions about causation justified? (5) External validity — can findings be generalised to other populations or settings? (6) Face validity — does the measure appear to measure what it claims to?
Internal validity is the extent to which a study's design controls for confounding variables and justifies causal claims — i.e., that the observed effects are due to the independent variable, not extraneous factors. It is most relevant in experimental research. Threats to internal validity include selection bias, maturation effects, testing effects, and instrument decay.
Reliability in quantitative research is measured using: (1) Cronbach's alpha — measures internal consistency of a scale (α ≥ 0.7 is generally acceptable); (2) Test-retest reliability — the same measure applied to the same group at two time points should yield similar results; (3) Inter-rater reliability — the degree of agreement between different observers or coders; (4) Split-half reliability — the scale is split in two and scores on both halves are correlated.
In qualitative research, the parallel concepts are 'trustworthiness' criteria (Lincoln & Guba, 1985): (1) Credibility (equivalent to internal validity) — member checking, prolonged engagement, triangulation; (2) Transferability (external validity) — thick description, purposive sampling; (3) Dependability (reliability) — audit trail, methodology documentation; (4) Confirmability (objectivity) — reflexivity, audit trail. More recently, Braun & Clarke's quality criteria for thematic analysis are also widely used.