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Qualitative Comparative Analysis (QCA) is a technique, originally developed by Charles Ragin in 1987. QCA currently has more adherents in Europe than in the United States. It is used for analyzing data sets by listing and counting all the combinations of variables observed in the data set, and then applying the rules of logical inference to determine which descriptive inferences or implications the data supports. In the case of categorical variables, QCA begins by listing and counting all types of cases which occur, where each type of case is defined by its unique combination of values of its independent and dependent variables. For instance, if there were four categorical variables of interest, , and A and B were dichotomous, C could take on five values, and D could take on three, then there would be 60 possible types of observations determined by the possible combinations of variables, not all of which would necessarily occur in real life. By counting the number of observations that exist for each of the 60 unique combination of variables, QCA can determine which descriptive inferences or implications are empirically supported by a data set. Thus, the input to QCA is a data set of any size, from small-N to large-N, and the output of QCA is a set of descriptive inferences or implications the data supports. In QCA's next step, inferential logic or boolean algebra is used to simplify or reduce the number of inferences to the minimum set of inferences supported by the data. This reduced set of inferences is termed the "prime implicants" by QCA adherents. For instance, if the presence of conditions A and B is always associated with the presence of a particular value of D, regardless of the observed value of C, then the value that C takes is irrelevant. Thus, all five inferences involving A and B and any of the five values of C may be replaced by the single descriptive inference "(A and B) implies the particular value of D". To establish that the prime implicants or descriptive inferences derived from the data by the QCA method are causal requires establishing the existence of causal mechanism using another method such as process tracing, formal logic, intervening variables, or established multidisciplinary knowledge.〔(qualitative comparative analysis - History Of qualitative comparative analysis | Encyclopedia.com: Dictionary Of Sociology )〕 The method is used in social science and is based on the binary logic of Boolean algebra, and attempts to ensure that all possible combinations of variables that can be made across the cases under investigation are considered. ==Objective== The technique of listing case types by potential variable combinations assists with case selection by making investigators aware of all possible case types that would need to be investigated, at a minimum, if they exist, in order to test a certain hypothesis or to derive new inferences from an existing data set. In situations where the available observations constitute the entire population of cases, this method alleviates the small N problem by allowing inferences to be drawn by evaluating and comparing the number of cases exhibiting each combination of variables. The small N problem arises when the number of units of analysis (e.g. countries) available is inherently limited. For example: a study where countries are the unit of analysis is limited in the fact that are only a limited number of countries in the world (less than 200), less than necessary for some (probabilistic) statistical techniques. By maximizing the number of comparisons that can be made across the cases under investigation, causal inferences are according to Ragin possible.〔J. Goldthorpe, "Current issues in comparative macrosociology" in ''Comparative social research'', 16, 1997, pp. 1-26.〕 This technique allows the identification of multiple causal pathways and interaction effects that may not be detectable via statistical analysis that typically requires its data set to conform to one model. Thus, it is the first step to identifying subsets of a data set conforming to particular causal pathway based on the combinations of covariates prior to quantitative statistical analyses testing conformance to a model; and helps qualitative researchers to correctly limit the scope of claimed findings to the type of observations they analyze. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Qualitative comparative analysis」の詳細全文を読む スポンサード リンク
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