Triangulation design validating quantitative data model

Triangulation facilitates validation of data through cross verification from more than two sources.It tests the consistency of findings obtained through different instruments and increases the chance to control, or at least assess, some of the threats or multiple causes influencing our results.This brief focuses on using mixed methods to evaluate patient-centered medical home (PCMH) models.It is part of a series commissioned by the Agency for Healthcare Research and Quality (AHRQ) and developed by Mathematica Policy Research under contract, with input from other nationally recognized thought leaders in research methods and PCMH models.It can lead to multi-perspective meta-interpretations. Notwithstanding validation and verification which are secondary, triangulation presents diverse perspectives on a specific issue using different investigative means to provide and enriched approach and outcome to the subject matter.The field of mixed methods has only been widely accepted for the last decade, though researchers have long been using multiple methods, just not calling them “mixed.” Mixed methods research takes advantage of using multiple ways to explore a research problem.

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Mixed methods research originated in the social sciences and has recently expanded into the health and medical sciences including fields such as nursing, family medicine, social work, mental health, pharmacy, allied health, and others.

MM practitioners promote the development of a theory-based set of three hypotheses.

Hypotheses should be conducted a priori and be both logical and sequential research questions (for more information, see Onwuegbuzie & Leech, 2006).

In the last decade, its procedures have been developed and refined to suit a wide variety of research questions (Creswell and Plano Clark, 2011).

These procedures include advancing rigor, offering alternative mixed methods designs, specifying a shorthand notation system for describing the designs to increase communication across fields, visualizing procedures through diagrams, noting research questions that can particularly benefit from integration, and developing rationales for conducting various forms of mixed methods studies.

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