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Quantitative designs

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  • Great presentation: I'm refining my ability to design studies and having to review which methods are appropriate/ a lot of this is still marinating ... :)
    I'm working on my DBA (dreams of PHD!) with a MPA (Tribal Governance).....
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    Quantitative designs Quantitative designs Presentation Transcript

    • Quantitative Research Designs and Methods Notes from McMillan & Schumacher EDUU600
    • Credibility of Research Design
      • Goal of sound research design
      • Provide results that approximate reality
      • Judged trustworthy and reasonable
      • Eliminate or reduce sources of error
      • Extraneous effects need to be controlled
    • Sources of Variability
      • Observations take on different values
      • Systematic
        • Two variables have high variability
        • Maximize
      • Error
        • Sampling and Measurement Errors
        • Minimize
    • Design Validity
      • Degree to which scientific explanations of phenomena match the realities of the world.
      • Internal Validity
        • Extent to which extraneous variables have been controlled and accounted for
      • External Validity
        • Generalizability of the results
        • The extent to which the results and conclusions can be generalized to other people and other settings
    • Designing Quantitative Research
      • Who will be assessed? – SUBJECTS
      • What will they be assessed by – INSTRUMENTS
      • How will they be assessed – PROCEDURES FOR DATA COLLECTION
      • In Experimental Designs – How are treatments administered?
    • Plausible Rival Hypotheses
      • Is there anything that has occurred or was done that could provide an explanation that is in addition to the stated hypothesis or intent of the research?
    • Possible Sources of Error
      • Does the researcher have an existing bias about subjects or topic researched?
      • Are the subjects aware that they are being studied?
      • Are the subjects responding honestly?
      • Did both groups receive treatment as described?
      • Does the sex of the interviewer matter?
      • Did very many subjects drop out before the end of the study?
      • Did the time of day the research was done affect the results?
    • Population
      • Group of elements or cases (individuals, objects, events) that conform to specific criteria
      • Group to which we intend to generalize the results of the research
      • Target population or Universe
    • Sample of Population- Probability Sampling
      • Subjects drawn from a larger population
      • Estimate what is true from a smaller sample of the general population
      • Representative of the population
      • Unbiased random sample
      • Each member of the population has the same chance of being selected as other members of the group
      See page 178-179
    • Simple Random Sampling
      • Drawing names out of a hat
      • Table of random numbers – set of randomly assorted digits
        • Each person randomly assigned a number from 001 to ?
        • Computer software random selection
    • Systematic Sampling
      • Every n th element selected from list
      • Weakness in sampling technique
        • when numbers arranged in systematic pattern
        • rank order,
        • by school, age, scores, etc.
      1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
    • Stratified Random Sampling
      • Population divided into subgroups on basis of strata (age, gender, level of education, etc.)
      • Proportional sampling – according to number in strata
      • Nonproportional sampling – equal numbers between strata
      • Cluster Sampling
        • Groups of individuals are identified from population
        • Subjects are drawn from this group
    • Nonprobability Sampling
      • Convenience Sampling
        • Accessible subjects
        • Convenience group – classroom of students, members of a group
      • Purposeful Sampling
        • Judgment sampling
        • Population that will be informative or representative about a topic
      • Quota Sampling
        • Select subjects on a basis of certain characteristics of the population
        • Profiles of groups identified and selected non-randomly
    • Sample Size
      • Number of subjects in a study
      • What size of sample will provide sufficient data to answer research question?
      n=120 n=35 n=3
    • Factors to take into consideration
      • Type of research
        • Correlational – minimum of 30
        • Comparing Groups – at least 15
        • Survey – At least 100
      • Research hypothesis
        • Small differences – large sample
        • Relatively small – but perhaps significant differences
      • Financial Constraints
    • Other Considerations
      • Importance of Results
        • Exploratory – smaller sample size
        • When major potential effect on people or $$ spent – need large enough sample to minimize error
      • Number of variables studied – more variables mean larger sample
      • Methods of data collection – accuracy or consistency
      • Larger the population, the smaller the percentage needed
    • Test Validity
      • Extent to which inferences and uses made on the basis of scores from an instrument are reasonable and appropriate
      • Appropriateness of measure for specific inferences, decisions, consequences or uses that results from scores are generated
      • Dependent on the purpose, population, situational factors
      • Mental Measurements reports technical information about instrument validity in terms of generalization
    • Test Reliability
      • Consistency of the measurement
      • Extent to which scores are similar over different forms of the same instrument
      • Scores consistent over different occasions of data collection
      • Minimize the influence on the scores of change or other variables unrelated to intent of the measure
    • Internal Validity of Design
      • Control over extraneous variables
      • Controls for error
      • Source of errors – “threats”
      • Threats may invalidate the study’s findings
      • Various Sources of Threats
    • Threats to Internal Validity
      • History
        • Incidents and events that occur during the research
        • Can occur within the study when something outside or unrelated happens during the treatment in an experiment
        • Outside the research setting
    • Threats
      • Selection
        • Systematic difference in groups
        • Existing differences
        • Volunteers – different characteristics
      • Statistical Regression – tendency for very high or low scores in pretest to regress to the mean on posttest
      • Pretesting – Test itself has impact on subjects
        • Stimulate thought
        • Change attitude toward topic
    • More Validity Threats
      • Instrumentation
        • The way the instrument is used to collect data
        • The person who uses the instrument
        • Fatigue, boredom, way of recording data
      • Subject Attrition – mortality or loss of subjects during course of study
      • Maturation –
        • Changes in subjects over a period of extended time
        • Fatigue, boredom, concentration, hunger, time of day
    • Threats, continued
      • Diffusion of Treatment - When control group/experimental group becomes aware of differences in treatment
      • Experimenter Effects
        • Deliberate and intentional effect on subjects
        • Tone of voice, gender, race, educational level, clothing, attitude of experimenter
    • More Threats to Internal Validity
      • Treatment Replications
        • Number of subjects in study is not the same as the number of treatments
        • Comparing 2 classes – n=2 but number of students may be 60.
        • Group assignment - but individual treatment for each student
      • Statistical Conclusion – “use of impressive-sounding statistics does not guarantee valid results” (pp. 192-193)
    • Subject Effects
      • Change behavior because they are being studied
      • Hawthorne effect – increase positive behavior because they know they are being studied
      • John Henry effect – Group tried harder to compete with other group (compensatory rivalry)
      • Resentful demoralization – not selected for the group with preferred treatment
      • Novelty effect – React with increased motivation because they are doing something new and different