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Understanding Research Design

Understanding Research Design. Can have confusing terms Research Methodology The entire process from question to analysis Research Design Clearly defined structures within which the study is implemented Is a large blueprint, but must be tailored to the study and then mapped out in detail.

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Understanding Research Design

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  1. Understanding Research Design • Can have confusing terms • Research Methodology • The entire process from question to analysis • Research Design • Clearly defined structures within which the study is implemented • Is a large blueprint, but must be tailored to the study and then mapped out in detail

  2. Quantitative Design Concerns • Primary purpose (check question) • Is there a treatment (intervention) • Will the treatment be controlled • Is there a control group (untreated) • Is there a pre or post test (or both) • Is the sample a random sample • Will the sample be a single group or divided into several groups

  3. Quantitative Design Concerns-2 • How many groups will there be • What is the size of each group • Will groups be randomly assigned • Will there be repeated measurements • Will the data be collected cross-sectionally or over time • Have extraneous variables been identified and controlled for • What strategies are being used for comparison of variables or groups

  4. Study Validity • Def: It is an examination of the approximation of truth or falsity of the propositions • Statistical Validity • Internal Validity • Construct Validity • External Validity • (Cook and Campbell, 1979)

  5. Statistical Validity Errors • Violate assumptions about the data • Nominal, ordinal, interval, ratio data • Type I and Type II errors • Need for Power Analysis • Predicts the necessary N value • Inappropriate use of certain statistics for the various types of data • Random irrelevancies in setting • Random heterogeneity of respondents

  6. Numbers and Use of Numbers • Nominal (qualitative) • A Named category given a number for convenience, e.g. males are 1 and females are 2 • Ordinal (qualitative) • A scale that is subjective but shows a direction, e.g. pain scale, cancer staging • Interval (quantitative) • Numbers where the interval between them is meaningful, e. g. a temperature • Ratio (quantitative) • Numbers where the ratio to each other has meaning, e. g. a pulse, heart rate.

  7. Statistical Conclusion ValidityType I and Type II Errors Accept the Null Hypothesis Reject the Null Hypothesis Reality is: Type I Error No Wanted There is no difference difference caused by fishing Reality is: Type II Error, there is There is a difference often caused Wanted Difference by a low N value

  8. Internal Validity • Definition: *It is the extent to which the effects detected in the study are a true reflection of reality rather than the result of extraneous variables; * The independent variable did have an impact on the dependent variable

  9. Threats to Internal Validity • History: Natural events over time impacting the subjects • Maturation: A person’s growth in any area impacting his/her response • Testing effect caused by subjects remembering previous testing • Instrument reliability of treatment • Selection process (randomized) • Mortality threat • Interaction with subjects • No equalization of treatment

  10. External Validity • Definition: To provide development of the design that allows it to be generalized beyond the sample used in the study. Most serious threat is that it can only be said of the group being studied

  11. Threats to External Validity • Small N • No randomization when it is needed • Special probability sampling • Simple • Stratified • Clustered • Systematic • Single vs. replicated

  12. Quantitative Designs • Experimental (Solomon) • Quasi-experimental • Descriptive • Case Study • Correlational

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