Psych 231: Research Methods in Psychology Non-Experimental designs: Surveys, Correlational & Quasi-experimental designs Psych 231: Research Methods in Psychology

Non-Experimental designs Sometimes you just can’t perform a fully controlled experiment Because of the issue of interest Limited resources (not enough subjects, observations are too costly, etc). Surveys Correlational studies Quasi-Experiments Developmental designs Small-N designs This does NOT imply that they are bad designs Just remember the advantages and disadvantages of each Non-Experimental designs

Stages of survey research Stage 1) Identify the focus of the study and select your research method Stage 2) Determining the research schedule and budget Stage 3) Establishing an information base Stage 4) Identify the sampling frame Stage 5) Determining the sample method and sampling size Review Probability and Non-Probability methods Voluntary response method Importance of sample size Stages of survey research

Importance of sample size Sampling error - how is the sample different from the population? Response rate What proportion of the sample actually responded to the survey? Hidden costs here - what can you do to increase response rates Non-response error (bias) Is there something special about the data that you’re missing (From the people who didn’t respond)? Importance of sample size

Importance of sample size Sampling error - how is the sample different from the population? Confidence intervals An estimate of the mean or percentage of the population, based on the sample data “John Doe has 55% of the vote, with a margin of error ± 3%” Margin of error (that “± 3%” part) The larger your sample size, the smaller your margin of error will be. Which would you be more likely to believe “We asked 10 people …” “We asked 1000 people …” Importance of sample size

Stages of survey research cont. Stage 6) Designing the survey instrument Question construction: How the questions are written is very important Clearly identify the research objectives Do your questions really target those research objectives (think Internal and External Validity)? Take care wording of the questions Keep it simple, don’t ask two things at once, avoid loaded or biased questions, etc. How should questions be answered (question type)? Stages of survey research cont.

Good and poor questions Was the FDC negligent by ignoring the warnings about Vioxx during testing and approving it for sale? Yes No Unsure Do you favor eliminating the wasteful excess in the public school budget? If the FDC knew that Vioxx caused serious side effects during testing, what should it have done? Ban it from ever being sold Require more testing before approving it Unsure Do you favor reducing the public school budget? Yes No Problem: emotionally charged words Good and poor questions

Good and poor questions Should senior citizens be given more money for recreation centers and food assistance programs? Yes No Unsure Should senior citizens be given more money for recreation centers? Yes No Unsure Should senior citizens be given more money for food assistance programs? Problem: asks two different questions Good and poor questions

Good and poor questions Are you against same sex marriage and in favor of a constitutional amendment to ban it? Yes No Unsure What is your view on same sex marriage? I think marriage is a matter of personal choice I’m against it but don’t want a constitutional amendment I want a constitutional amendment banning it Problem: Biased in more than one direction Problem: Asks two questions Good and poor questions

Survey Questions Question types Open-ended (fill in the blank, short answer) Can get a lot of information, but Coding is time intensive and potentially ambiguous Close-ended (pick best answer, pick all that apply) Easier to code Response alternatives are the same for everyone Rating scales Used for “how much” judgments e.g., measures attitudes, agree/disagree Take care with your labels Range of scores, anchors Survey Questions

Survey Questions Closed-ended Open-ended What is the best thing about ISU? (choose one) 1. Location 2. Academics 3. Dorm food 4. People who sell things between Milner and the Bone What is the best thing about ISU? Survey Questions

Survey Questions if closed-ended decide number/label of response alternatives should use odd number (5 or 7 best) labels should be clear decide scale rating: PSY 231 is an important course in the major. 1 2 3 4 5 Strongly Agree Neutral Disagree Strongly Agree Disagree Survey Questions

Survey Questions if closed-ended decide scale semantic differential: PSY 231 Important _____: _____: _____: _____: _____: Unimportant Boring _____: _____: _____: _____: _____: Interesting nonverbal scale for children: Point to the face that shows how you feel about the toy. Survey Questions

Stages of survey research cont. Stage 7) Pre-testing the survey instrument Fix what doesn’t seem to be working Stage 8) Selecting and training interviewers For telephone and in-person surveys Need to avoid interviewer bias Stage 9) Implementing the survey Stage 10) Coding and entering the data Stage 11) Analyzing the data and preparing a final report Stages of survey research cont.

Non-Experimental designs Sometimes you just can’t perform a fully controlled experiment Because of the issue of interest Limited resources (not enough subjects, observations are too costly, etc). Surveys Correlational Quasi-Experiments Developmental designs Small-N designs This does NOT imply that they are bad designs Just remember the advantages and disadvantages of each Non-Experimental designs

Correlational designs Looking for a co-occurrence relationship between two (or more) variables Used for Descriptive research do behaviors co-occur? Predictive research is one behavior predictive of another? Reliability and Validity Does your measure correlate with others (and itself)? Evaluating theories Look for co-occurrence posited by the theory. Correlational designs

Correlational designs Looking for a co-occurrence relationship between two (or more) variables Example 1: Suppose that you notice that the more you study for an exam, the better your score typically is. This suggests that there is a relationship between study time and test performance. We call this relationship a correlation. 3 properties: form, direction, strength Correlational designs

Y X 1 2 3 4 5 6 Hours study X Exam perf. Y 6 1 2 5 3 4 Scatterplot

Linear Non-linear Form

Direction Positive Negative Y X Y X X & Y vary in the same direction X & Y vary in opposite directions Y X Direction

r = 0.0 “no relationship” r = 1.0 “perfect positive corr.” r = -1.0 “perfect negative corr.” -1.0 0.0 +1.0 The farther from zero, the stronger the relationship Strength

Rel A Rel B r = -0.8 r = 0.5 -.8 .5 -1.0 0.0 +1.0 Which relationship is stronger? Rel A, -0.8 is stronger than +0.5 Strength

Y X 1 2 3 4 5 6 For our example, we have a linear relationship, it is positive, and fairly strong Scatterplot

Correlational designs Looking for a co-occurrence relationship between two (or more) variables Explanatory variables (Predictor variables) Response variables (Outcome variables) Example 1: Suppose that you notice that the more you study for an exam, the better your score typically is For our example, which variable is explanatory and which is response? And why? It depends on your theory of the causal relationship between the variables Correlational designs

Scatterplot Y 6 5 4 3 2 1 X Response (outcome) variable For descriptive case, it doesn’t matter which variable goes where Correlational analysis For predictive cases, put the response variable on the Y axis Regression analysis Explanatory (predictor) variable Scatterplot

Correlational designs Advantages: Doesn’t require manipulation of variable Sometimes the variables of interest can’t be manipulated Allows for simple observations of variables in naturalistic settings (increasing external validity) Can look at a lot of variables at once Correlational designs

Correlational designs Disadvantages: Don’t make casual claims Third variable problem Temporal precedence Coincidence (random co-occurence) Correlational results are often misinterpreted Correlational designs

Misunderstood Correlational designs Disadvantages: Example 2: Suppose that you notice that kids who sit in the front of class typically get higher grades. This suggests that there is a relationship between where you sit in class and grades. Daily Gazzett Children who sit in the back of the classroom receive lower grades than those who sit in the front. Possibly implied: “[All] Children who sit in the back of the classroom [always] receive worse grades than [each and every child] who sits in the front.” Better: “Researchers X and Y found that children who sat in the back of the classroom were more likely to receive lower grades than those who sat in the front.” Misunderstood Correlational designs Example from Owen Emlen (2006)

Quasi-experiments What are they? General types Almost “true” experiments, but with an inherent confounding variable General types An event occurs that the experimenter doesn’t manipulate Something not under the experimenter’s control (e.g., flashbulb memories for traumatic events) Interested in subject variables high vs. low IQ, males vs. females Time is used as a variable Quasi-experiments

Quasi-experiments Advantages Disadvantages Allows applied research when experiments not possible Threats to internal validity can be assessed (sometimes) Disadvantages Threats to internal validity may exist Designs are more complex than traditional experiments Statistical analysis can be difficult Most statistical analyses assume randomness Quasi-experiments

Quasi-experiments Program evaluation Research on programs that is implemented to achieve some positive effect on a group of individuals. e.g., does abstinence from sex program work in schools Steps in program evaluation Needs assessment - is there a problem? Program theory assessment - does program address the needs? Process evaluation - does it reach the target population? Is it being run correctly? Outcome evaluation - are the intended outcomes being realized? Efficiency assessment- was it “worth” it? The the benefits worth the costs? Quasi-experiments

Quasi-experiments Nonequivalent control group designs with pretest and posttest (most common) (think back to the second control lecture) participants Experimental group Control Measure Non-Random Assignment Independent Variable Dependent Variable But remember that the results may be compromised because of the nonequivalent control group (review threats to internal validity) Quasi-experiments

Quasi-experiments Interrupted & Non-interrupted time series designs Observe a single group multiple times prior to and after a treatment Obs Obs Obs Obs Treatment Obs Obs Obs Obs Look for an instantaneous, permanent change Interrupted – when treatment was not introduced by researcher, for example some historical event Variations of basic time series design Addition of a nonequivalent no-treatment control group time series O O O T O O O & O O O _ O O O Interrupted time series with removed treatment If treatment effect is reversible Quasi-experiments