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10 Experimental research.docx

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Carleton University
PSYC 2001
Guy Lacroix

Experimental research Experimental research designs - Aresearch strategy that attempts to establish the existence of a cause-and-effect relationship between two variables by manipulating one variable while measuring the second variable and controlling all other variables • Rubin (1970) – Relation between love and gazing • Davis et al. (2001) – Ternus task and dyslexia • Rosenthal and Lawson (1964) – “Dull and bright” rats • Gauthier et al. (1999) – Prosopagnosia study - Science is a method of knowledge acquisition that: • Addresses empirically solvable problems; • Uses systematic empiricism; • Allows its findings to be publicly verified. - Experimental research designs are the pinnacle of systematic empiricism Designing an experimental study - Research question. Does time spent studying lead to better academic performance? - Does time spent studying cause better academic performance? - Operationalization • What is “time spent studying”? • What is “academic performance”? Operationalized constructs and hypothesis - Academic performance. Ability to recall 50 definitions in Gravetter and Forzano (2009) • External validity • Case study • Sample - Time spent studying. • 2 hours • 4 hours - Hypothesis. Participants who study for 4 hours will recall more definitions on a test than participants who study for 2 hours. “But it’s not real life” revisited - Experimental psychologists know that it is better to have “limited” causal explanations, than generalizable, but vague explanations. Increases Internal validity Experimental research designs Decreases External validity PSYC 2001 – Introduction to Research Methods 1 Independent variable - The variable manipulated by the researcher. The variable controlled to ascertain cause - The thing you’re going to control, vary, manipulate to see its cause on the dependent variable The levels of the independent variable - The number of treatment conditions to which participants are exposed. Dependent variable - The variable that is observed for changes in order to assess the effects of manipulating the independent variable. Extraneous and potential confounding variables - How can we guarantee that other variables are not causing changes in the grades? Random assignment - Aprocedure in which a random process is used to assign participants to treatment conditions. - Must randomly assign participants to conditions - Idea is that there will be all types of conditions within each group, they are no longer confounding variables Matching - The assignment of individuals to groups so that a specific variable is balanced or matched across the groups. Statistical control - It is possible to mathematically remove the contribution of a variable using anAnalysis of Covariance (ANCOVA). - You enter an IQ score for everyone, and remove the IQ... leave the difference in study time. **** Environmental variables - How can we guarantee that environmental variables are not causing changes in the grades? Control - We make the testing conditions across participants as similar as possible. Causal explanation - If 4 hours of study does lead to better results than 2 hours, then we can say that study time does cause better performance (independently of other variables). - This will be true independently of other variables Four important questions - How do experimental designs deal with the directionality problem? • One is free to vary, but the other is controlled • Directionality problem is when you don’t know what caused what. By having independent and dependent variables, you are only controlling one and you can see how the changes affect the second variable. - How do experimental designs deal with the third-variable problem? • Third variable is when you’re not sure if independent variable is actually changing the dependent variable, and that it is being caused by a third variable. this design eliminates this problem because of all the control placed on experiment eliminates as much as possible that there is a third variable causing the changes - Do experimental designs guarantee that the most significant independent variable(s) have been selected for study? • No, all we can guarantee is that it does seem to have a causal effect if it has a significant effect - Do experimental designs guarantee that all threats to internal validity have been eliminated? • No, no experimental design can be 100% factual. There could always be something affecting things somehow • No because it is impossible to run a perfect experiment Two basic experimental designs - For many experiments, the researcher has a choice. Will participants be tested in only one condition or will they be tested in all conditions? - ½ go in 1 group, the other ½ goes in the other - This is called a between-group design *****???? - Every participant gets every level of the independent variable Two basic experimental designs - Between-subjects or independent-measures experimental design: An experimental design using separate, independent groups of individuals for each treatment condition being compared. - Independent Groups design: every participant gets a single level of a single variable - T-value: statistic you’re testing to see if its significant or not - P-value: the smaller the better • Looking at the probability that the results are due to chance Advantages and inconveniences of between-subjects designs - Advantages • No practice effects  If you are doing 1 level of independent variable... you are doing it once • May limit fatigue or boredom effects (because you are only doing 1 condition) - Inconveniences • Limited power (requires a larger number of participants than other designs) • If you only have 2 sources of errors ***** it makes the test less .... ***** • More expensive – more labor intensive Using more than two levels of an independent variable - Theoretical motivation leads researchers to create designs with more than two levels of a given independent variable (1, 2, or 3 hours) Using more than two levels of an independent variable Correct answers 50 e n 40 c 30 r 20 C 10 0 1 hour 2 hours 3 hours Hours of study - Do we use t-tests to compare 1 with 2, 1 with 3, and 2 with 3? - To avoid Type I error (claiming that there is a significant difference when there isn’t), Analyses of Variance (ANOVAs) are used. - When you run inferential statistics, you increase
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