Research Lecture2 Research Approaches

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  • Research Lecture2 Research Approaches

    1. 1. Research Methods Lecture 2 Non-experimental and Experimental Research Approaches Chapters 2 & 3
    2. 2. Research Designs/Approaches Gender differences in visual/spatial abilities Moderate to high Current or past Test for cause/ effect relationships without full control Quasi-experi-mental Comparing two types of treatments for anxiety. High current Test for cause/ effect relationships Experi-mental Examples Degree of control Time frame Purpose Type
    3. 3. Research Designs/Approaches Relationship between history of child abuse & depression. Low to medium Past & current Examine the effect of past event on current functioning. Ex post facto Relationship between studying style and grade point average. Low to medium Current (cross-sectional) or past Examine relationship between two variables Non-experimental - corre-lational Examples Degree of control Time frame Purpose Type
    4. 4. Research Designs/Approaches How mother-child negativity changed over adolescence. Low to moderate Future Examine change in a var. over time in overlapping groups. Cohort-sequen-tial Relat. betw. history of depression & development of cancer. Low to moderate Future -predictive Examine relat. betw. 2 var. where 1 is measured later. Non-experimental -corre-lational Examples Degree of control Time frame Purpose Type
    5. 5. Research Designs/Approaches People’s experiences of quitting smoking. None or Low Past or current Discover potential relationships; descriptive. Quali-tative Voting preferences before an election. None or low Current Assess opinions or characteristics that exist at a given time. Survey Examples Degree of control Time frame Purpose Type
    6. 6. Non-experimental Research Designs <ul><li>Describes a particular situation or phenomenon. </li></ul><ul><li>Hypothesis generating </li></ul><ul><li>Can describe effect of implementing actions based on experimental research and help refine the implementation of these actions. </li></ul>
    7. 7. Correlational Design <ul><li>Measure two variables </li></ul><ul><ul><li>Study methods and grade-point average </li></ul></ul><ul><li>Determine degree of relationship between them </li></ul><ul><ul><li>Correlation coefficient (e.g., r = 0.50) </li></ul></ul><ul><li>Allows description and prediction of the relationship </li></ul>
    8. 8. Correlational Studies <ul><li>Type of descriptive research design </li></ul><ul><ul><li>Advantage is that it can examine variables that cannot be experimentally manipulated (e.g., IQ and occupational status). </li></ul></ul><ul><ul><li>Disadvantage is that it cannot determine causality. </li></ul></ul><ul><ul><li>Third variable may account for the association. </li></ul></ul><ul><ul><li>Directionality unclear </li></ul></ul>
    9. 9. Origins of the Correlation Coefficient Children’s height Parent’s height Correlation between parent’s height and children’s height 2 3 4 6 4 3 65” 6 8 11 11 8 6 66” 10 13 14 13 11 7 67” 2 12 12 10 6 3 68” 9 9 8 5 3 2 69” 5 5 4 2 70” 69” 68” 67” 66” 65” 64”
    10. 10. Correlation Scatterplot Strong Positive Relationship
    11. 11. Correlation Scatterplot Strong Negative Relationship
    12. 12. Correlational Designs <ul><li>What are some correlational studies that you can do? </li></ul>
    13. 13. Ex Post Facto Study <ul><li>Variable of interest is not subject to direct manipulation but must be chosen after the fact. </li></ul><ul><li>E.g., Define two groups of people according to a certain characteristic (e.g., history of trauma) and measure how they respond in terms of anxiety to a certain stimulus (e.g., watching violent film). </li></ul><ul><li>Limitation – self-selection bias, cohort effects may explain the effect. </li></ul>
    14. 14. Personality and Hypertension, Effect of Hypertension Awareness
    15. 15. Personality and Hypertension: Effect of Hypertension Awareness 89 89 75 75 % Male 118.5/ 75.7 (10.3/4.8) 135.8/ 93.8 (8.2/3.4) 118.7/ 76.3 (11.5/5.5) 135.1/ 93.9 (9.2/5.1) SBP/DBP Mean* (SD) 45.8 (8.0) 46.4 (8.3) 46.2 (8.2) 46.2 (9.2) Age Mean* (SD) Group 4 Normo-tensive Group 3 Unaware Hyper-tensive Group 2 Normo-tensive Group 1 Aware Hyper-tensive Variable
    16. 16. Personality and Hypertension: Effect of Hypertension Awareness * Group 1 > Group 2 & Group 3 (p < 0.01) -2.6 (8.2) -2.0 (9.4) -3.0 (9.4) 0.79 (8.5) Type A Mean* (SD) 9.5 (4.6) 9.7 (4.8) 9.3 (5.3) 12.0 (5.3) Neuro-ticism Mean* (SD) Group 4 Normo-tensive Group 3 Unaware Hyper-tensive Group 2 Normo-tensive Group 1 Aware Hyper-tensive Variable
    17. 17. Personality and Hypertension: Effect of Hypertension Awareness Aware hypertensive > normotensive & unaware hypertensive, P < 0.001
    18. 18. Personality and Hypertension: Conclusion <ul><li>Do hypertensives have a different personality than those with normal blood pressure? </li></ul><ul><ul><li>No, because the unaware hypertensives did not differ from the normotensives. </li></ul></ul><ul><li>Why did the aware and unaware hypertensives differ? </li></ul><ul><ul><li>Possible explanations? </li></ul></ul>
    19. 19. Personality and Hypertension: Conclusion <ul><li>Awareness of hypertension status confounds assessment of the association between personality characteristics and hypertension. </li></ul><ul><ul><li>Due to hypertension labeling effect; or </li></ul></ul><ul><ul><li>Due to self-selection bias </li></ul></ul>
    20. 20. Cross-Sectional Study Designs <ul><li>Compares groups at one point in time </li></ul><ul><ul><li>E.g., age groups, ethnic groups, disease groups. </li></ul></ul><ul><li>Advantage is that it is an efficient way to identify possible group differences because you can study them at one point in time. </li></ul><ul><li>Disadvantage is that you cannot rule out cohort effects. </li></ul>
    21. 21. Longitudinal Design <ul><li>Gathers data on a factor (e.,g. confidence) over time. </li></ul><ul><li>Advantage is that you can see the time course of the development or change in the variables </li></ul><ul><ul><li>Confidence increasing with age. </li></ul></ul><ul><ul><li>Confidence increasing at a faster rate in the 30’s than the 40’s. </li></ul></ul><ul><ul><li>Confidence decreasing in the 50’s and 60’s. </li></ul></ul><ul><ul><li>Disadvantage is it is costly and still subject to bias </li></ul></ul>
    22. 22. Cohort-Sequential Design <ul><li>Combines a bit of the cross-sectional design and longitudinal design </li></ul><ul><ul><li>E.g., Different age groups are compared on a variable over time. </li></ul></ul><ul><li>Advantage – very efficient and reduces some of the biases in the cross-sectional design since you can see the evolution of change over time. </li></ul><ul><li>Disadvantage – cannot rule out cohort bias or the problem of the ‘unidentified’ third variable accounting for the change. </li></ul>
    23. 23. Naturalistic Observation <ul><li>Aims to unobtrusively observe behaviour in the natural setting. </li></ul><ul><li>Observing in the natural setting enables one to minimize or eliminate the problem of artificial behaviour in response to being studied (i.e., reactivity effects). </li></ul><ul><li>One variation is being a participant observer (e.g., undercover agent). </li></ul>
    24. 24. Naturalistic Observation <ul><li>Advantages </li></ul><ul><ul><li>Observe the natural phenomena (not artificial) </li></ul></ul><ul><li>Disadvantages </li></ul><ul><ul><li>Observer bias </li></ul></ul><ul><ul><li>Reactivity in subjects </li></ul></ul><ul><ul><li>Ethics </li></ul></ul>
    25. 25. Meta Analysis (Glass 1976) <ul><li>Quantitative approach to integrate and describe results across a range of independent studies. </li></ul><ul><li>Enables you to combine the probability (p) value for statistical tests over a number of studies. </li></ul><ul><li>Enables you to determine the effect size of the independent variable (e.g., treatment group) across studies. </li></ul>
    26. 26. Survey Research <ul><li>Collecting standarized information from people using an interview or self-report format. </li></ul><ul><li>Typically survey knowledge or opinions. </li></ul><ul><li>To standarized the information one uses a questionnaire with set questions. </li></ul><ul><li>Ideally the questionnaire has been validated. </li></ul><ul><li>Representativeness of the sample is very important. </li></ul>
    27. 27. Survey Methods <ul><li>Interviews </li></ul><ul><ul><li>Advantage - Comprehensive, ensure participant understands the question, minimizes missing data, enables clarification of unclear responses </li></ul></ul><ul><ul><li>Disadvantage – expensive, people more like to refuse participation, can be risky for interviewer, interviewer may bias the responses. </li></ul></ul>
    28. 28. Types of Survey Methods <ul><li>Face-to-face interviews </li></ul><ul><ul><li>Expensive and time-consuming </li></ul></ul><ul><li>Telephone interviews </li></ul><ul><ul><li>Need to use random-digit dialing to reach both listed and unlisted numbers. </li></ul></ul><ul><li>Mail </li></ul><ul><ul><li>Return rate is usually low (20-30%). </li></ul></ul>
    29. 29. Types of Questions <ul><li>Open-ended </li></ul><ul><ul><li>E.g., Can you tell me about your typical experience with dating? </li></ul></ul><ul><li>Close-ended </li></ul><ul><ul><li>E.g., How do you typically meet someone to date? </li></ul></ul><ul><ul><ul><li>Introduced by someone </li></ul></ul></ul><ul><ul><ul><li>Social event </li></ul></ul></ul><ul><ul><ul><li>In university class or place of work </li></ul></ul></ul><ul><ul><ul><li>At a bar </li></ul></ul></ul><ul><ul><ul><li>Through sports or other athletic events </li></ul></ul></ul>
    30. 30. Sampling <ul><li>Population is everyone in your population of interest. </li></ul><ul><li>Sample is some proportion of the population. </li></ul><ul><li>Haphazard sampling – convenience sample </li></ul><ul><li>Random sampling </li></ul><ul><ul><li>There is always some degree of sampling error. </li></ul></ul>
    31. 31. Qualitative Methods <ul><li>Multimethod approach to studying people in their natural environment </li></ul><ul><ul><li>It is interpretive – researcher has to make sense of the data </li></ul></ul><ul><ul><li>Multimethod – can use interviews, photographs, natural observation, archives, etc. </li></ul></ul><ul><ul><li>It is typically conducted in person’s natural environment. </li></ul></ul><ul><li>Valuable to use when phenomenon not fully defined. </li></ul>
    32. 32. Qualitative Methods Limitations <ul><li>Participant’s observations and accounts can be biased. For example, filtered by his/her style of expression, gender, social class, race, age, ethnicity, etc. </li></ul><ul><li>People are seldom able to provide a true and full account of their experience. </li></ul><ul><ul><li>Defensive </li></ul></ul><ul><ul><li>Lack insight </li></ul></ul><ul><ul><li>Unaware </li></ul></ul>
    33. 33. Qualitative Methods Transcripts
    34. 34. Experimental Designs <ul><li>Examines differences between experimentally manipulated groups or variables (e.g., one group gets a certain drug and the other gets a placebo). </li></ul><ul><li>At minimum, experimental (independent) variable has two levels (e.g., drug vs. placebo). </li></ul><ul><ul><li>Advantage is that you can determine causality. </li></ul></ul><ul><ul><li>Disadvantage is cost and many variables cannot be experimentally manipulated (e.g., smoke exposure over time). </li></ul></ul>
    35. 35. Experimental Designs Four Canons for Identifying Causality <ul><li>Method of Agreement – </li></ul><ul><ul><li>Observe the element common to several instances of the event </li></ul></ul><ul><ul><li>Problem is you may inadvertently overlook a significant variable. </li></ul></ul><ul><li>Method of Difference – </li></ul><ul><ul><li>Identify the different effects produced by two situations that are alike in all ways but one. </li></ul></ul><ul><ul><li>Fairly robust and strong method. </li></ul></ul>
    36. 36. Experimental Designs Four Canons for Identifying Causality <ul><li>Joint methods of agreement and difference </li></ul><ul><ul><li>Observe the element common to several instances of the event </li></ul></ul><ul><ul><li>Form hypothesis based on observations </li></ul></ul><ul><ul><li>Test hypothesis using method of difference </li></ul></ul><ul><li>Method of Concomitant Variation – </li></ul><ul><ul><li>Identify the different effects produced by more than two situations that are alike in all ways but one. </li></ul></ul><ul><ul><li>E.g., Compare two active drugs to a placebo </li></ul></ul>
    37. 37. Experimental Design <ul><li>Because it is so difficult with human behaviour to demonstrate causation unequivocally, some argue that a theory or prediction can only achieve the status of “not yet disconfirmed” (Popper, 1968). </li></ul><ul><li>Our scientific efforts are directed at finding the causal factors rather than ‘the cause’ per se. </li></ul>
    38. 38. Psychological Experiment: Is Objective <ul><li>Researcher strives for freedom from bias. </li></ul><ul><li>Recognize that: </li></ul><ul><ul><li>Mistakes can occur </li></ul></ul><ul><ul><li>Carefully scrutinize all steps of the experiment to identify where mistakes are likely. </li></ul></ul><ul><ul><li>Take the steps necessary to minimize error. </li></ul></ul>
    39. 39. Psychological Experiment: Focuses on a Phenomenon <ul><li>This is a publicly observable behaviour. </li></ul><ul><ul><li>Actions </li></ul></ul><ul><ul><li>Appearances </li></ul></ul><ul><ul><li>Verbal statements </li></ul></ul><ul><ul><li>Responses to questionnaires </li></ul></ul><ul><ul><li>Physiological responses. </li></ul></ul>
    40. 40. Psychological Experiment: Is Done Under Strictly Controlled Conditions <ul><li>Eliminate all factors that could influence the outcome other than the factor being manipulated. </li></ul><ul><li>Control is needed to infer causation. </li></ul><ul><li>All conditions are kept constant except one; the manipulated variable. </li></ul><ul><li>The variable of interest is varied in order to test its effect. </li></ul>
    41. 41. Experimental Method <ul><li>Advantages </li></ul><ul><ul><li>Strength with which causal relationships can be inferred. </li></ul></ul><ul><ul><li>Ability to manipulate one or more variables. </li></ul></ul><ul><ul><li>Proven to be a very useful and robust scientific method (i.e., withstood the test of time). </li></ul></ul>
    42. 42. Experimental Method <ul><li>Disadvantages </li></ul><ul><ul><li>Tight controls often produce artificial conditions that could limit the generalizability of the findings (i.e., internal vs. external validity trade-off). </li></ul></ul><ul><ul><li>Time consuming. </li></ul></ul><ul><ul><li>Expensive. </li></ul></ul><ul><ul><li>Human behaviour is very complex and cannot be fully studied using experimental methods. </li></ul></ul>
    43. 43. Experimental Method: Threats to Internal Validity <ul><li>Learning or practice effects </li></ul><ul><ul><li>Scores on a measure change on repeat testing because participant has more familiarity with the measure and so answers more truthfully. </li></ul></ul><ul><li>Natural history effects </li></ul><ul><ul><li>Something happens in the social background (e.g., society because more affluent generally) and this influences the participant’s responses. </li></ul></ul><ul><li>Maturation </li></ul><ul><ul><li>Natural developments in the participant account for the changes (e.g., getting older). </li></ul></ul>
    44. 44. Experimental Method: Threats to Internal Validity <ul><li>Regression to the mean </li></ul><ul><ul><li>High scores generally move down toward the mean and low scores move up. </li></ul></ul><ul><li>Instrumentation </li></ul><ul><ul><li>If pre and post tests are not equivalent in all ways (e.g., difficulty, readability) then differences observed may be due to ‘instrumentation’ differences rather than due to your experimental manipulation. </li></ul></ul>
    45. 45. Experimental Method: Threats to Internal Validity <ul><li>Subject problems </li></ul><ul><ul><li>Selection bias (e.g., participation rate). </li></ul></ul><ul><ul><li>Attrition (e.g., only motivated subjects stay in the experiment). </li></ul></ul>
    46. 46. Experimental Method: Threats to External Validity <ul><li>Subject variables </li></ul><ul><ul><li>Selection bias. </li></ul></ul><ul><ul><li>Attrition bias </li></ul></ul><ul><li>Artificial conditions </li></ul><ul><ul><li>E.g., In order to measure a subject’s blood pressure in response to a well-fined stressor you bring him/her into the laboratory but his/her response in the laboratory may not reflect how his/her blood pressure would really respond under stress in his natural environment. </li></ul></ul>
    47. 47. Let me know… <ul><li>If there are any topics from today’s lecture that need fuller explanations. </li></ul><ul><li>Anything you particularly liked about the lecture (today’s or others as we go along). </li></ul><ul><li>Anything you particularly disliked about the lecture (today’s or others as we go along). </li></ul>

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