Guidelines for Qualitative Interview and Data Analysis

It'stempting to think that qualitative analysis of text (analysis oftext without any recourse to coding and counting) keeps yousomehow "close to the data." I've heard a lot of thiskind of talk, especially on e-mail lists about working withqualitative data.

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 (the two quotes are from Miles & Huberman (1994, p. 40). Qualitative Data Analysis)

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However, it is not necessary to pit these two paradigms against one another in a competing stance. Patton ( ) advocates a "paradigm of choices" that seeks " as the primary criterion for judging methodological quality." This will allow for a "situational responsiveness" that strict adherence to one paradigm or another will not (p. 39). Furthermore, some researchers believe that qualitative and quantitative research can be effectively combined in the same research project ( ). For example, Russek and Weinberg ( ) claim that by using both quantitative and qualitative data, their study of technology-based materials for the elementary classroom gave insights that neither type of analysis could provide alone.

Qualitative Data, Quantitative Analysis

A common practice of investigators is to defer the selection of analytic procedure to a research team ‘statistician’. Ideally, investigators should have substantially more than a basic understanding of the rationale for selecting one method of analysis over another. This can allow investigators to better supervise staff who conduct the data analyses process and make informed decisions

While methods of analysis may differ by scientific discipline, the optimal stage for determining appropriate analytic procedures occurs early in the research process and should not be an afterthought. According to Smeeton and Goda (2003), “Statistical advice should be obtained at the stage of initial planning of an investigation so that, for example, the method of sampling and design of questionnaire are appropriate”.

The chief aim of analysis is to distinguish between an event occurring as either reflecting a true effect versus a false one. Any bias occurring in the collection of the data, or selection of method of analysis, will increase the likelihood of drawing a biased inference. Bias can occur when recruitment of study participants falls below minimum number required to demonstrate statistical power or failure to maintain a sufficient follow-up period needed to demonstrate an effect (Altman, 2001).

When failing to demonstrate statistically different levels between treatment groups, investigators may resort to breaking down the analysis to smaller and smaller subgroups in order to find a difference. Although this practice may not inherently be unethical, these analyses should be proposed before beginning the study even if the intent is exploratory in nature. If it the study is exploratory in nature, the investigator should make this explicit so that readers understand that the research is more of a hunting expedition rather than being primarily theory driven. Although a researcher may not have a theory-based hypothesis for testing relationships between previously untested variables, a theory will have to be developed to explain an unanticipated finding. Indeed, in exploratory science, there are no a priori hypotheses therefore there are no hypothetical tests. Although theories can often drive the processes used in the investigation of qualitative studies, many times patterns of behavior or occurrences derived from analyzed data can result in developing new theoretical frameworks rather than determined (Savenye, Robinson, 2004).

It is conceivable that multiple statistical tests could yield a significant finding by chance alone rather than reflecting a true effect. Integrity is compromised if the investigator only reports tests with significant findings, and neglects to mention a large number of tests failing to reach significance. While access to computer-based statistical packages can facilitate application of increasingly complex analytic procedures, inappropriate uses of these packages can result in abuses as well.

Every field of study has developed its accepted practices for data analysis. Resnik (2000) states that it is prudent for investigators to follow these accepted norms. Resnik further states that the norms are ‘…based on two factors:

Data in this study will be analysed using a qualitative content analysis procedure.
For the qualitative article, I will identify the design of the article, the methods used and the strategies used for analyzing the data....

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Over the last decades, archives of qualitative data have become widely accessible to research-es and there has been a smaller revolution in the practice of secondary analysis on such data.

Qualitative Data Analysis

1/11 Qualitative data analysis

Qualitative interviews may be used either as the primary strategy for data collection, or in conjunction with observation, document analysis, or other techniques ( ). Qualitative interviewing utilizes open-ended questions that allow for individual variations. Patton ( ) writes about three types of qualitative interviewing: 1) informal, conversational interviews; 2) semi-structured interviews; and 3) standardized, open-ended interviews.

Qualitative data analysis is:

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In fact, in the phrases"qualitative data analysis" and "quantitative dataanalysis," it is impossible to tell if the adjectives"qualitative" and "quantitative" modify thesimple noun "data" or the compound noun "dataanalysis." It turns out, of course, that both QDA phrasesget used in both ways.