How to ensure reliability and validity in quantitative research

Quantitative research relies on the reliability and validity of its data. Reliability is all about consistency. In other words, however many times you measure something the results should always be the same. Validity is different. A test, for example, is valid if it can measure what it is designed to measure.

 

Validity and reliability are the watch words which underpin all research:

In the past the humanities were not really concerned about these constructs, but now all research demands rigour and reliability and validity in quantitative research as well as qualitative research is of paramount importance.

Your work should be reliable and valid so that other researchers can replicate your study and discover whether or not your data is reliable and valid.

Ways of establishing research is valid and reliable

Here is a list of the general methods that are used to establish the validity of a research study.

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Reliability means in part that measurements are consistent and in turn this means that if the exact same conditions prevail in another study, for example, then the same results should be obtained. When the results are reproducible, then this is a measure of reliability. This helps to demonstrate that the results of a study are trustworthy. A study can be replicated time after time to determine the reliability of the original research methods, for example.

Researchers, for this reason, have a duty to the scientific community to report their methodology, results and findings honestly.

Next let’s look at the idea of falsifiability: this basically means that if any hypothesis has credence it has to be possible to test whether or not is correct. All researchers should test their hypotheses and prove or disprove them before they disseminate the results of their study. If a theory cannot be tested others working in the same field will not be convinced of its worth or the scientific rigour of the study. Replication must be possible to test the study’s validity. If a study cannot be replicated, this might lead other researchers to believe that the results were fabricated, and this would invalidate the whole study.

Results and findings should also be generalisable. If the results are generalisable other researchers can interpret findings and apply them to broader contexts. This makes them both relevant and more meaningful.

Some ways of establishing validity and reliability are: -

  1. Statistical analysis involves the collection of data and exploring it in order to work out what trends and patterns there are.
  2. Data triangulation adds weight to your research study because a researcher can use evidence from various sources and comparing it. This strengthens the research you have undertaken because you can compare data from interviews, documents, observations photographs and public documents, for example.
  3. Theory triangulation is also valuable as it enables the researcher to use various theoretical approaches to support and interpret data.
  4. Feedback – this is important because not everyone will hold the same opinions or have exactly the same experiences in a given situation.

To begin with, the more sources of information you use, the richer will be your data. The different sources you use will provide you with more insight into your chosen study area.

It could be that one of your sources is not very reliable, so it is always necessary to check that several different sources confirm the same findings or results. When different sources confirm your data, then you know that it is valid and reliable.

When you employ data triangulation methods, you end up with more comprehensive data and when it is supported in various research studies and in different types of research, then it is easier to analyse your data set and draw conclusions regarding the outcomes of your research.

Perhaps one of the biggest benefits of triangulation is that you can more easily identify any inconsistencies in your data.

To measure construct validity, you can utilise three types of evidence: -

  • Homogeneity - The tool or instrument is only measuring one construct.
  • Convergence – can only be used when the instrument or tool is measuring concepts that are similar to those measured by other instruments. However, this might not be possible if there are no other similar instruments available.
  • Theory evidence – this can be utilised when, for example, a person’s behaviour is very similar to theoretical propositions that are measured by the instrument. An example might be that if an instrument is designed to measure levels of anxiety, it would be reasonable to expect that participants in a study who score highly on the anxiety scale would also show symptoms of anxiety in their everyday existences.

Criterion validity can be measured in three basic ways: -

  1. Convergent validity: - this demonstrates that an instrument has a mutual connection with another. It basically means that you have to demonstrate that concepts which should theoretically be related actually are.
  2. Divergent validity: - this demonstrates that a tool or instrument is not very well correlated to other instruments or tools that are designed to measure different variables.
  3. Predictive validity: - how far can you predict results? For example, if a participant in a study scores highly in self-efficacy, this should mean that he or she should quite easily complete a simple task set by the researcher. Predictive validity can be used by employers to predict performance at work-based tasks, based on test scores.

Quantitative research relies heavily on statistics, numbers, tables and other mathematical tools. It might include scientific experiments, or clinical trials, data collection using questionnaires, surveys or interviews that can be transcribed and coded in order to get a comprehensive picture of a social phenomenon using by interviewing samples of the population. Surveys are staples of quantitative researchers. The survey can be conducted in a variety of ways, each of which have certain drawbacks.

Have you ever been asked to take part in a survey? What was your response to the person trying to conduct the survey? Would you necessarily be honest in your responses? This, of course, is assuming that you were asked to be a part of a market research survey conducted on the street. Most people are so busy going about their business that they often don’t have time to answer an interviewer’s questions. So how relevant is this type of survey and what does it imply about the results gathered?

How can interviewers ensure that there is a representative sample in terms of age, ethnicity and gender, for example?

Using a questionnaire also poses problems. If you want to conduct a large-scale study, you might consider posting the questionnaire to specific addresses. However, there is no guarantee that your chosen respondents will complete your questionnaire and send it back to you. More often than not, unsolicited mail goes straight into the waste paper bin.

Of course, you could devise an online survey and email it to targeted respondents, but again it will probably end up in the spam box or will be sent to trash, without the intended recipient ever opening the email.

Then there are telephone interviews which are equally problematic. No one likes cold-callers and so the phone is put down unceremoniously in most cases, unless there is a lonely elderly person on the end of the phone who may not be in the right age group for your target sample. Also, the cost of telephone calls can make this kind survey very expensive.

Using questionnaires or surveys, however, are often the preferred methods of data collection for quantitative studies.

If you use these methods of data collection, you may find that you need to employ several people to help you with the coding of responses.

It is all very well to come up with an interviewing tool but then you have to decide on what closed questions you need to know the answers to. It will not be possible to ask open-ended questions because of the diverse answers that will be given. This means that your data will not be as rich as it might have been if you had more time to conduct your study and if you had many interviewers to assist in your data collection.

On the other hand, qualitative research tools do yield some rich data, but samples tend to be small, so the findings might not be generalisable.

Interviews are usually highly structured in quantitative research studies and the researcher doesn’t deviate from his or her standard set of questions. When conducting interviews in this way, much information may be lost.

The face-to-face interview gives the researcher time to establish some kind of rapport with the respondent, and this could mean that he or she is more cooperative. In fact, it is these kinds of interviews that produce the highest, and most interesting response rates in surveys. They are useful because any misunderstandings can be cleared up immediately as long as the interviewer is allowed to ask follow-up questions and probe ambiguities. However, the downside to such interviews is that they aren’t really feasible with large samples and perhaps time is of the essence.

Using Skype to conduct interviews can help enormously as long as respondents are online. The cost of such interviews is minimal, and interviewers and respondents can interact face-to-face, if both agree to do so. One drawback of the telephone or Skype interviews is that only respondents with telephones or Skype can participate in the survey, which might mean that they are from one of the upper social classes.

Perhaps you could consider Computer Assisted Personal Interviewing (CAPI), which entails the interviewer going along to the scheduled interview with a laptop or small computer and entering responses directly into his or her laptop. Although this saves the interviewer carrying hundreds of printed questionnaires around, it can be expensive to set up.

In fact, there is no best way to gather either quantitative or qualitative data.

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