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      A tutorial on Bayes factor estimation with the product space method

      , , , , ,
      Journal of Mathematical Psychology
      Elsevier BV

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          Diary methods: capturing life as it is lived.

          In diary studies, people provide frequent reports on the events and experiences of their daily lives. These reports capture the particulars of experience in a way that is not possible using traditional designs. We review the types of research questions that diary methods are best equipped to answer, the main designs that can be used, current technology for obtaining diary reports, and appropriate data analysis strategies. Major recent developments include the use of electronic forms of data collection and multilevel models in data analysis. We identify several areas of research opportunities: 1. in technology, combining electronic diary reports with collateral measures such as ambulatory heart rate; 2. in measurement, switching from measures based on between-person differences to those based on within-person changes; and 3. in research questions, using diaries to (a) explain why people differ in variability rather than mean level, (b) study change processes during major events and transitions, and (c) study interpersonal processes using dyadic and group diary methods.
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            A survey method for characterizing daily life experience: the day reconstruction method.

            The Day Reconstruction Method (DRM) assesses how people spend their time and how they experience the various activities and settings of their lives, combining features of time-budget measurement and experience sampling. Participants systematically reconstruct their activities and experiences of the preceding day with procedures designed to reduce recall biases. The DRM's utility is shown by documenting close correspondences between the DRM reports of 909 employed women and established results from experience sampling. An analysis of the hedonic treadmill shows the DRM's potential for well-being research.
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              Bayes Factors

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                Author and article information

                Journal
                Journal of Mathematical Psychology
                Journal of Mathematical Psychology
                Elsevier BV
                00222496
                October 2011
                October 2011
                : 55
                : 5
                : 331-347
                Article
                10.1016/j.jmp.2011.06.001
                5063a8a4-c98b-4964-ac59-1abf4a50ef12
                © 2011

                http://www.elsevier.com/tdm/userlicense/1.0/

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