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The data collection instrument used in content analysis is the codebook or coding scheme. In qualitative content analysis the codebook is constructed and improved during coding, while in quantitative content analysis the codebook needs to be developed and pretested for reliability and validity before coding. [4]
While content analysis is often quantitative, researchers conceptualize the technique as inherently mixed methods because textual coding requires a high degree of qualitative interpretation. [3] Social scientists have used this technique to investigate research questions concerning mass media, [1] media effects [4] and agenda setting. [5]
According to Krippendorf, [34] "Content analysis is a research technique for making replicable and valid inference from data to their context" (p. 21). It is applied to documents and written and oral communication. Content analysis is an important building block in the conceptual analysis of qualitative data. It is frequently used in sociology.
Human factors, human work capital is important issue that deals with qualitative properties. Some common aspects are work, motivation, general participation, etc. Although all of these aspects are not measurable in terms of quantitative criteria, the general overview of them could be summarized as a quantitative property.
Computer-assisted (or aided) qualitative data analysis software (CAQDAS) offers tools that assist with qualitative research such as transcription analysis, coding and text interpretation, recursive abstraction, content analysis, discourse analysis, [1] grounded theory methodology, etc.
For quantitative analysis, data is coded usually into measured and recorded as nominal or ordinal variables.. Questionnaire data can be pre-coded (process of assigning codes to expected answers on designed questionnaire), field-coded (process of assigning codes as soon as data is available, usually during fieldwork), post-coded (coding of open questions on completed questionnaires) or office ...
Often, nomothetic approaches are quantitative, and idiographic approaches are qualitative, although the "Personal Questionnaire" developed by Monte B. Shapiro [2] and its further developments (e.g. Discan scale and PSYCHLOPS [3]) are both quantitative and idiographic.
In statistics, qualitative comparative analysis (QCA) is a data analysis based on set theory to examine the relationship of conditions to outcome. QCA describes the relationship in terms of necessary conditions and sufficient conditions . [ 1 ]