• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Research Lecture2 Research Approaches

Research Lecture2 Research Approaches






Total Views
Views on SlideShare
Embed Views



1 Embed 2

http://www.slideshare.net 2


Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
Post Comment
Edit your comment

Research Lecture2 Research Approaches Research Lecture2 Research Approaches Presentation Transcript

  • Research Methods Lecture 2 Non-experimental and Experimental Research Approaches Chapters 2 & 3
  • 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
  • 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
  • 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
  • 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
  • Non-experimental Research Designs
    • Describes a particular situation or phenomenon.
    • Hypothesis generating
    • Can describe effect of implementing actions based on experimental research and help refine the implementation of these actions.
  • Correlational Design
    • Measure two variables
      • Study methods and grade-point average
    • Determine degree of relationship between them
      • Correlation coefficient (e.g., r = 0.50)
    • Allows description and prediction of the relationship
  • Correlational Studies
    • Type of descriptive research design
      • Advantage is that it can examine variables that cannot be experimentally manipulated (e.g., IQ and occupational status).
      • Disadvantage is that it cannot determine causality.
      • Third variable may account for the association.
      • Directionality unclear
  • 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”
  • Correlation Scatterplot Strong Positive Relationship
  • Correlation Scatterplot Strong Negative Relationship
  • Correlational Designs
    • What are some correlational studies that you can do?
  • Ex Post Facto Study
    • Variable of interest is not subject to direct manipulation but must be chosen after the fact.
    • 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).
    • Limitation – self-selection bias, cohort effects may explain the effect.
  • Personality and Hypertension, Effect of Hypertension Awareness
  • 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
  • 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
  • Personality and Hypertension: Effect of Hypertension Awareness Aware hypertensive > normotensive & unaware hypertensive, P < 0.001
  • Personality and Hypertension: Conclusion
    • Do hypertensives have a different personality than those with normal blood pressure?
      • No, because the unaware hypertensives did not differ from the normotensives.
    • Why did the aware and unaware hypertensives differ?
      • Possible explanations?
  • Personality and Hypertension: Conclusion
    • Awareness of hypertension status confounds assessment of the association between personality characteristics and hypertension.
      • Due to hypertension labeling effect; or
      • Due to self-selection bias
  • Cross-Sectional Study Designs
    • Compares groups at one point in time
      • E.g., age groups, ethnic groups, disease groups.
    • Advantage is that it is an efficient way to identify possible group differences because you can study them at one point in time.
    • Disadvantage is that you cannot rule out cohort effects.
  • Longitudinal Design
    • Gathers data on a factor (e.,g. confidence) over time.
    • Advantage is that you can see the time course of the development or change in the variables
      • Confidence increasing with age.
      • Confidence increasing at a faster rate in the 30’s than the 40’s.
      • Confidence decreasing in the 50’s and 60’s.
      • Disadvantage is it is costly and still subject to bias
  • Cohort-Sequential Design
    • Combines a bit of the cross-sectional design and longitudinal design
      • E.g., Different age groups are compared on a variable over time.
    • Advantage – very efficient and reduces some of the biases in the cross-sectional design since you can see the evolution of change over time.
    • Disadvantage – cannot rule out cohort bias or the problem of the ‘unidentified’ third variable accounting for the change.
  • Naturalistic Observation
    • Aims to unobtrusively observe behaviour in the natural setting.
    • 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).
    • One variation is being a participant observer (e.g., undercover agent).
  • Naturalistic Observation
    • Advantages
      • Observe the natural phenomena (not artificial)
    • Disadvantages
      • Observer bias
      • Reactivity in subjects
      • Ethics
  • Meta Analysis (Glass 1976)
    • Quantitative approach to integrate and describe results across a range of independent studies.
    • Enables you to combine the probability (p) value for statistical tests over a number of studies.
    • Enables you to determine the effect size of the independent variable (e.g., treatment group) across studies.
  • Survey Research
    • Collecting standarized information from people using an interview or self-report format.
    • Typically survey knowledge or opinions.
    • To standarized the information one uses a questionnaire with set questions.
    • Ideally the questionnaire has been validated.
    • Representativeness of the sample is very important.
  • Survey Methods
    • Interviews
      • Advantage - Comprehensive, ensure participant understands the question, minimizes missing data, enables clarification of unclear responses
      • Disadvantage – expensive, people more like to refuse participation, can be risky for interviewer, interviewer may bias the responses.
  • Types of Survey Methods
    • Face-to-face interviews
      • Expensive and time-consuming
    • Telephone interviews
      • Need to use random-digit dialing to reach both listed and unlisted numbers.
    • Mail
      • Return rate is usually low (20-30%).
  • Types of Questions
    • Open-ended
      • E.g., Can you tell me about your typical experience with dating?
    • Close-ended
      • E.g., How do you typically meet someone to date?
        • Introduced by someone
        • Social event
        • In university class or place of work
        • At a bar
        • Through sports or other athletic events
  • Sampling
    • Population is everyone in your population of interest.
    • Sample is some proportion of the population.
    • Haphazard sampling – convenience sample
    • Random sampling
      • There is always some degree of sampling error.
  • Qualitative Methods
    • Multimethod approach to studying people in their natural environment
      • It is interpretive – researcher has to make sense of the data
      • Multimethod – can use interviews, photographs, natural observation, archives, etc.
      • It is typically conducted in person’s natural environment.
    • Valuable to use when phenomenon not fully defined.
  • Qualitative Methods Limitations
    • Participant’s observations and accounts can be biased. For example, filtered by his/her style of expression, gender, social class, race, age, ethnicity, etc.
    • People are seldom able to provide a true and full account of their experience.
      • Defensive
      • Lack insight
      • Unaware
  • Qualitative Methods Transcripts
  • Experimental Designs
    • Examines differences between experimentally manipulated groups or variables (e.g., one group gets a certain drug and the other gets a placebo).
    • At minimum, experimental (independent) variable has two levels (e.g., drug vs. placebo).
      • Advantage is that you can determine causality.
      • Disadvantage is cost and many variables cannot be experimentally manipulated (e.g., smoke exposure over time).
  • Experimental Designs Four Canons for Identifying Causality
    • Method of Agreement –
      • Observe the element common to several instances of the event
      • Problem is you may inadvertently overlook a significant variable.
    • Method of Difference –
      • Identify the different effects produced by two situations that are alike in all ways but one.
      • Fairly robust and strong method.
  • Experimental Designs Four Canons for Identifying Causality
    • Joint methods of agreement and difference
      • Observe the element common to several instances of the event
      • Form hypothesis based on observations
      • Test hypothesis using method of difference
    • Method of Concomitant Variation –
      • Identify the different effects produced by more than two situations that are alike in all ways but one.
      • E.g., Compare two active drugs to a placebo
  • Experimental Design
    • 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).
    • Our scientific efforts are directed at finding the causal factors rather than ‘the cause’ per se.
  • Psychological Experiment: Is Objective
    • Researcher strives for freedom from bias.
    • Recognize that:
      • Mistakes can occur
      • Carefully scrutinize all steps of the experiment to identify where mistakes are likely.
      • Take the steps necessary to minimize error.
  • Psychological Experiment: Focuses on a Phenomenon
    • This is a publicly observable behaviour.
      • Actions
      • Appearances
      • Verbal statements
      • Responses to questionnaires
      • Physiological responses.
  • Psychological Experiment: Is Done Under Strictly Controlled Conditions
    • Eliminate all factors that could influence the outcome other than the factor being manipulated.
    • Control is needed to infer causation.
    • All conditions are kept constant except one; the manipulated variable.
    • The variable of interest is varied in order to test its effect.
  • Experimental Method
    • Advantages
      • Strength with which causal relationships can be inferred.
      • Ability to manipulate one or more variables.
      • Proven to be a very useful and robust scientific method (i.e., withstood the test of time).
  • Experimental Method
    • Disadvantages
      • Tight controls often produce artificial conditions that could limit the generalizability of the findings (i.e., internal vs. external validity trade-off).
      • Time consuming.
      • Expensive.
      • Human behaviour is very complex and cannot be fully studied using experimental methods.
  • Experimental Method: Threats to Internal Validity
    • Learning or practice effects
      • Scores on a measure change on repeat testing because participant has more familiarity with the measure and so answers more truthfully.
    • Natural history effects
      • Something happens in the social background (e.g., society because more affluent generally) and this influences the participant’s responses.
    • Maturation
      • Natural developments in the participant account for the changes (e.g., getting older).
  • Experimental Method: Threats to Internal Validity
    • Regression to the mean
      • High scores generally move down toward the mean and low scores move up.
    • Instrumentation
      • 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.
  • Experimental Method: Threats to Internal Validity
    • Subject problems
      • Selection bias (e.g., participation rate).
      • Attrition (e.g., only motivated subjects stay in the experiment).
  • Experimental Method: Threats to External Validity
    • Subject variables
      • Selection bias.
      • Attrition bias
    • Artificial conditions
      • 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.
  • Let me know…
    • If there are any topics from today’s lecture that need fuller explanations.
    • Anything you particularly liked about the lecture (today’s or others as we go along).
    • Anything you particularly disliked about the lecture (today’s or others as we go along).