The Design and Interpretation of Social Science Research


In this discussion, we examine the design and interpretation of social science research. Select one of the following (individual differences, history effects, response bias, regression to the mean, experimenter bias, testing effects, or participant reactions) and discuss the impact on research design. Describe the issue and how it impacts the design considerations for the researcher. Explain how the issue impacts the estimation of validity and the interpretation of results.

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To me, bias is one of the major influences that can skew one’s research. Sometimes, the researcher themselves have biases that they are unaware they are implementing during their data collection, structuring of their surveys/interviews, sample choice, and even the interpretation process. Biases are not always intentional. There are 5 biases that Bhattacherjee (2012) briefly covers in his book: non-response bias, sampling bias, social desirability bias, recall bias, and common method bias. Non-response bias is due to receiving limited responses for collection, such as when conducting a survey. The issue of non-response bias is why the selected participants are not responding. The researcher needs to determine if there is a systematic issue such as people are more likely to report on negative experiences versus positive experiences. Another issue with non-response is the relevance the survey may have to the participant. Incentives, follow-up questions, endorsements, respondent-friendly questionnaires, and assurance of confidentiality and privacy increase the likelihood of obtaining a sample group of data that will not be biased (Bhattacherjee, 2012). Other aspects that can influence a participants response include environment, accessibility to the survey/questionnaire, who is conducting the interview, the mental/emotional state of the participant that day, etc. These are all biases that can skew the responses that participants give. The impact response biases have on the validity and interpretation of results can be astronomical. An example would be conducting a survey on how a particular city feels about emergency responders after a major incident. For instance, October 1 for the city of Las Vegas was a tragic day. As a resident, I remember some people being happy with the response of emergency responders, whereas others were upset about it. Most of those who were happy with the response were those directly affected by the tragedy. With that being a smaller group, which consisted largely of out-of-towners, their response would not be pertinent to how the city of Las Vegas feels. Therefore, the estimation of validity would be minimal and the interpretation may be incorrect.




Bhattacherjee, A. (2012) Social Science Research: Principles, Methods, and Practices. Pp 80- 82.



Response Bias is how participants answer the questions on surveys or questionnaires. Participants may not be honest about their responses. Response bias can happen for many reasons. From research and articles that I have read dealing with response bias, some bias can come from feeling pressured to answer a certain way. Bias can also happen when someone may feel that their identity will be somehow exposed causing them to give untruthful issues. Untruthful answers can come from fear and anxiety. Response bias can also happen if researcher privately offers incentives to answer questions a certain way.

Response Bias effects the validity of the research study negatively. When I say negatively I mean that even if the answers of the questionnaires are answered wrong to have a desired outcome it’s still negative because the study would be invalid due to the untruthfulness. This can lead to a study going in the wrong direction all together. Any untruthfulness leads to an invalid result.

There are ways that researchers can design research in order to make it as valid as possible. For starters, they can word surveys and questionnaires in a more neutral way. This will help make it appear that whatever answer the participant gives, it is okay. Surveys and questionnaires can be completely anonymous which can lead to more truthful answers. When things are made to be neutral and stripped of any type of branding, participants will more likely be able to answer truthfully, thus making the answers reliable and valid.




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