Questions What is the best way to avoid order effects while doing within subjects design? We talked about people becoming more depressed during a treatment.
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1 QuestionsWhat is the best way to avoid order effects while doing within subjects design?We talked about people becoming more depressed during a treatment period, but would a history effect also include if a participant became happier due to an outside factor other than the treatment being done?What is an example of participant attrition?When a study is being conducted, if a confounding variable was found, would the study make changes to control the confounding variable right away, or would they continue the study but note the confounding variable in the discussion?
2 More QuestionsHow do you determine how much time should pass between treatments to ensure that your counterbalancing is effective?I really don’t understand counterbalancing. Can you explain it in a really simplistic way?? Why would you use this method?Two groups going through the same treatments in different order – it is still a within subjects designDoes counterbalancing eliminate order effects?In matched-subject designs is the matching randomly assigned even though researchers are matching participants based on certain characteristics?
3 More QuestionsIs it possible to use other statistical analyses such as regression, Chi-square, F-test etc. rather than ANOVA and t-test in within-subjects or between-subjects designs?Regression – determines function of the best fit to your data (relationship between dependent and independent variables)Chi-square – data consisting of proportionsF-test (ANOVA) – t-test (two groups) as a special form of F-test (more than two groups)Analysis of covariance – ANCOVAMultivariate analysis of variance - MANOVACan the final be open notes? I wrote out all the key words, did all the exercises etc. I can’t memorize like that. Are you going to curve?
4 Chapter 10 Dusana Rybarova Psyc 290B May 26 2006 Nonexperimental and Quasi-Experimental Strategies: Nonequivalent Group, Pre-Post, and Developmental DesignsChapter 10Dusana RybarovaPsyc 290BMay
5 1. Introduction quasi-experimental research strategy like an experiment, typically involves a comparison of groups or conditionshowever, it uses a nonmanipulated variable to define groups or conditions being compared such as age, gender or time (before vs. after treatment)within the context of quasi-experimental research, the variable that is used to differentiate the groups of participants or the groups of scores being compared is called the quasi-independent variable (e.g. age)the variable that is measured to obtain a score for each individual is called the dependent variable (e.g. IQ score)
6 1. Introduction Nonexperimental research strategy Very similar to quasi-experimental research strategyMajor distinction – nonexperimental designs make little or no attempt to minimize threats to internal validityJust like in the quasi-experimental designs there is no real manipulation of variablesIn contrast to quasi-experimental designs there is less rigor in control of extraneous variables
7 1. Introduction in what follows we will use the following symbols X – represents the treatmentO – represents an observation or measurement2 groups of nonexperimental and quasi-experimental designs:Between-subjects designs or nonequivalent group designsWithin-subjects designs or pre-post designs
8 2. Nonequivalent group designs (between-subjects) nonequivalent group design is a research study in which the different groups of participants are formed under circumstances that do not permit the researcher to control the assignment of individuals to groups because those groups are pre-existing; the groups of participants are therefore considered nonequivalente.g. a researcher wants to evaluate a teen pregnancy prevention program by comparing the pregnancy rates in a high school where the program is used with pregnancy rates in a high school that does not use the program
9 2. Nonequivalent group designs nonequivalent group design has a built-in threat to internal validity that precludes an unambiguous cause-and-effect explanation, i.e. assignment biasthree examples of nonequivalent group designsthe differential research design (nonexperimental)the posttest-only nonequivalent control group design (nonexperimental)the pretest-posttest nonequivalent control group design (quasi-experimental)
10 2. Nonequivalent group designs the differential research design (nonexperimental)simply compares pre-existing groupsuses a participant characteristic such as gender, race, or personality to automatically assign participants to groupsno random assignment of participants to groupsdependent variable is then measured for each participant to obtain a set of scores within each groupthe goal of the study is to determine whether the scores for one group are consistently different from scores in another groupe.g. mother’s and father’s involvement in the peer relationships of their adolescent childrenin differential research, participant differences in one variable are used to create separate groups, and measurements of the second variable are made within each groupcorrelational study treats all the participants as a single group and simply measures the two variables for each individual
11 2. Nonequivalent group designs Post-test only nonequivalent control group design (nonexperimental)compares two nonequivalent groups of participantsone group is observed (measured) after receiving a treatment, and the other group is measured at the same time but receives no treatmentDoes not protect agains assignment biase.g. the teen pregnancy programX O (treatment group)O (nonequivalent control group)
12 2. Nonequivalent group designs Pretest-posttest nonequivalent control group design (quasi-experimental)compares two nonequivalent groupsone group is measured twice – once before a treatment and once afterProblem of assignment bias even though it is reduced by pre and post measurementPotential problems with differential history effects, differential instrumentation, differential testing effects, differential maturation and differential regressionthe other group is measured at the same two times but does not receive any treatmentO X O (treatment group)O O (nonequivalent control group)
13 3. Pre-post designs (within-subjects) series of observations is made over time on one group of subjectsInternal validity is threatened by time-related effectsone-group pretest-posttest design (nonexperimental)Each individual in a group is measured once before and once after a treatmentDoes not control for possible extraneous variables possibly causing change over timeO X Oe.g. evaluating the effectiveness of a new political TV commercial
14 3. Pre-post designs (within-subjects) time series and interrupted time-series designs (quasi-experimental)Series of observations for each participant before a treatment and a series of observations after the treatmentEliminates many problems with the pretest-postest design, outside events are a confound only if they occur simultaneously with the treatmentO O O X O O OTime series design – treatment administered by the researchere.g. anger management program for studentsInterrupted time-series design – event or treatment is not created by the researchere.g. legal change
15 3. Pre-post designs (within-subjects) Equivalent time-sample design (quasi-experimental)Consists of a long series of observations during which a treatment is alternately administered and then withdrawnOOOXOOONOOOXOOONOOOXOOON…N – no treatmentIt reduces likelihood of an external event confound to the treatmentDifferences between expected temporary and permanent effects
16 4. Developmental research designs the purpose is to describe the relationship between age and other variablesCross-sectional research design (nonexperimental)uses different groups of individuals, each group representing a different agethe different groups are measured at one point in time and then compared (e.g. IQ in 30, 40, 50 and 60 years old)individuals who were born at roughly the same time and grew up under similar circumstances are called cohortsthe terms cohort effect or generation effect refer to a difference between age groups (or cohorts) due to unique characteristics or experiences other than age; generation effects are a type of third-variable problem
17 4. Developmental research designs Longitudinal research design (nonexperimental)examines development by making a series of observations or measurements over timecommonly the same group of individuals is followed and measured at different points in timeAvoids problems with cohort effects but is usually very time-consuming and expensiveSerious problem with participant attritione.g. follow-up on IQ changes in the same group of subjects when they are 20 years old, 30, 40 and 50 years old