Types of reliability and how to measure them

When you do quantitative research, you have to consider the reliability and validity of your methods and instruments of measurement.

Reliability tells you how consistently a method measures something. When you apply the same method to the same sample under the same conditions, you should get the same results. If not, the method of measurement may be unreliable.

There are four main types of reliability. Each can be estimated by comparing different sets of results produced by the same method.

Type of reliabilityMeasures the consistency of…
Test-retestThe same test over time.
InterraterThe same test conducted by different people.
Parallel formsDifferent versions of a test which are designed to be equivalent.
Internal consistencyThe individual items of a test.

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What is content analysis and how can you use it in your research?

Content analysis is a research method used to identify patterns in recorded communication. To conduct content analysis, you systematically collect data from a set of texts, which can be written, oral, or visual:

  • Books, newspapers and magazines
  • Speeches and interviews
  • Web content and social media posts
  • Photographs and films

Content analysis can be both quantitative (focused on counting and measuring) and qualitative (focused on interpreting and understanding). In both types, you categorize or “code” words, themes, and concepts within the texts and then analyze the results.

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Reliability vs validity: what’s the difference?

Reliability and validity are concepts used to evaluate the quality of research. They indicate how well a method, technique or test measures something. Reliability is about the consistency of a measure, and validity is about the accuracy of a measure.

It’s important to consider reliability and validity when you are creating your research design, planning your methods, and writing up your results, especially in quantitative research.

Reliability vs validity
What does it tell you?The extent to which the results can be reproduced when the research is repeated under the same conditions.The extent to which the results really measure what they are supposed to measure.
How is it assessed?By checking the consistency of results across time, across different observers, and across parts of the test itself.By checking how well the results correspond to established theories and other measures of the same concept.
How do they relate?A reliable measurement is not always valid: the results might be reproducible, but they’re not necessarily correct.A valid measurement is generally reliable: if a test produces accurate results, they should be reproducible.

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The main types of research compared

When you start planning a research project, developing research questions and creating a research design, you will have to make various decisions about the type of research you want to do.

There are many ways to categorize different types of research. The words you use to describe your research depend on your discipline and field. In general, though, the form your research design takes will be shaped by:

  • The type of knowledge you aim to produce
  • The type of data you will collect and analyze
  • The sampling methods, timescale and location of the research

This article takes a look at some common distinctions made between different types of research and outlines the key differences between them.

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Internal vs external validity

When testing cause-and-effect relationships, validity can be split up into two types: internal and external validity.

Internal validity refers to the degree of confidence that the causal relationship being tested is trustworthy and not influenced by other factors or variables.

External validity refers to the extent to which results from a study can be applied (generalized) to other situations, groups or events.

The validity of a study is largely determined by the research design: what, how, where and when the study was executed.

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Descriptive research

Descriptive research aims to accurately and systematically describe a population, situation or phenomenon. It can answer what, when, where, when and how questions, but not why questions. To determine cause and effect, experimental research is required.

A descriptive research design can use a wide variety of quantitative and qualitative methods to investigate one or more variables. Unlike in experimental research, the researcher does not control or manipulate any of the variables, but only observes and measures them.

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How to do a case study

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods, but quantitative methods are sometimes also used. Case studies are good for describing, comparing, evaluating and understanding different aspects of a research problem.

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Correlational research

A correlational research design measures a relationship between two variables without the researcher controlling either of them. It aims to find out whether there is either:

Positive correlationBoth variables change in the same directionAs height increases, weight also increases
Negative correlationThe variables change in opposite directionsAs coffee consumption increases, tiredness decreases
Zero correlationThere is no relationship between the variablesCoffee consumption is not correlated with height

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How to transcribe an interview

Transcribing is converting speech to text word for word. Transcribing is a common practice when conducting interviews because it enables you to perform analysis.

How to transcribe an interview in five steps:

  1. Choose between verbatim, intelligent verbatim, or edited transcription
  2. Transcribe the audio (use transcription software)
  3. Add speaker designation and time stamps
  4. Clarify the transcript where needed
  5. Proofread the transcript

Transcription software comparison

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Inductive vs. deductive reasoning

Inductive reasoning aims at developing a theory. It moves from specific observations to broad generalizations. Deductive reasoning aims at testing an existing theory. It moves from broad generalizations to specific observations.

Both approaches are used in various types of research, and it’s not uncommon to combine them in one large study.

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