rigor and interpretation for quantitative research

  1. quantitative results
    • the statistical results of a study, in and of themselves, do not communicate much meaning
    • statistical results must be interpreted to be use to clinicians and other researchers
  2. interpretive task involves addressing what 6 considerations
    • the credibility and accuracy of the results
    • the precision of the estimate of effects
    • the magnitude of effects and importance 
    • the meaning of the results
    • the generalizability of the results 
    • the implications of the results for practice, theory, further research
  3. inference
    • - An inference is that act of drawing conclusions based on limited information, using logical reasoning
    • - Inferences about the real world are valid, however, to the extent that the researchers have made rigorous methodological decisions in selecting proxies and have controlled sources of bias
  4. interpretation
    interpretation research findings involves making a series of inferences
  5. the interpretive mindset
    • approach the task of interpretation with a critical - and even skeptical - mindset
    • test the "null hypotheses" that they are right
    • show me!!! expect researchers to provide strong evidence that their results are credible - i.e., that the "null hypotheses" has no merit.
  6. inferences of the type the researcher wishes people to make are supported by what?
    • rigorous methodological decisions
    • good proxies or stand-ins for abstract constructs and idealized methods
    • minimization of threats to study validity 
    • elimination or reduction of bias
    • efforts to find corroboration evidence
  7. CONSORT guidelines
    • reporting guidelines have been developed so that readers better evaluate methodologic decisions and outcomes 
    • the Consolidated Standards of Reporting Trials [CONSORT] include a flow chart for documenting participant flow in a study
  8. precision and magnitude
    • results should be interpreted in light og the precision if the estimates [often communicated through confidence intervals] and magnitude of effects [effect sizes]
    • considered especially important to clinical decision-making

    • precision: reported by confidence intervals
    • magnitude: how strongly and important they are
  9. meaning and causality
    great caution is needed in drawing casual inferences - especially when the study is experimental [and cross-sectional]

  10. Meaning and hypotheses
    greatest challenges to interpreting the meaning of results: nonsginificant result, serendipitous significant results, mixed results

    because statistical procedures are designed to provide support for research hypotheses through the rejection of the null hypotheses, testing a research hypothesis that  is a null hypothesis is very dificult
  11. type 1 error
    you reject the null hypothesis when its actually true. Your said that there’s relationship, but you were wrong. You should have supported the null hypothesis [in and dep variable have no relationship] [false-pos error]
  12. type 2 error
    you've accepted the null hypothesis [isn’t a relationship between the ind. And dep. Variable], but actually there is a relationship. [false-neg]
Card Set
rigor and interpretation for quantitative research
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