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Causal research, also called explanatory research. is the investigation of (research into) cause-and-effect relationships.〔Brains, C., Willnat, L,, Manheim, J., Rich, R. 2011. ''Empirical Political Analysis'' 8th edition. Boston, MA: Longman. p. 76.〕〔(【引用サイトリンク】 title=Causal research )〕 In order to determine causality, it is important to observe variation in the variable that is assumed to cause the change in the other variable(s), and then measure the changes in the other variable(s). Other confounding influences need to be controlled for so they don't distort the results, either by holding them constant in the experimental creation of data, or by using statistical methods. This type of research is very complex and the researcher can never be completely certain that there are not other factors influencing the causal relationship, especially when dealing with people’s attitudes and motivations. There are often much deeper psychological considerations that even the respondent may not be aware of. There are two research methods for exploring the cause-and-effect relationship between variables: # Experimentation (e.g., in a laboratory), and # Statistical research. ==Experimentation== (詳細はphysics, for example, use this approach. Alternatively, field experiments can be performed, as with medical studies in which subjects may have a great many attributes that cannot be controlled for but in which at least the key hypothesized causative variables can be varied and some of the extraneous attributes can at least be measured. Field experiments also are sometimes used in economics, such as when two different groups of welfare recipients are given two alternative sets of incentives or opportunities to earn income and the resulting effect on their labor supply is investigated. 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「Causal research」の詳細全文を読む スポンサード リンク
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