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McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved. Choosing a Research Design.

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Presentation on theme: "McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved. Choosing a Research Design."— Presentation transcript:

1 McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved. Choosing a Research Design

2 2 Two activities of scientific study Exploratory data collection and analysis Classifying behavior Identifying important variables Identifying relationships among variables Hypothesis testing Evaluating explanations for observed relationships Begins after enough information collected to form testable hypotheses

3 3 Causal relationship One variable directly or indirectly causes changes in another Can be unidirectional (Changes in A cause changes in B, but not the other way around) Can be bidirectional (Changes in A cause changes, but changes in B cause changes in A) Correlational relationship Changes in one variable accompany changes in another Such covariation does not mean that changes in one variable cause changes in another

4 4 No independent variables are manipulated Two or more dependent variables are measured, and a relationship is established Correlational relationships can be used for predictive purposes A PREDICTOR VARIABLE can be used to predict the value of a CRITERION VARIABLE Correlational research cannot be used to establish causal relationships among variables

5 5 Two reasons why you should not infer causality from correlational data Third-variable problem There may be an unmeasured variable that actually causes changes in observed behavior Directionality problem Not always possible to specify the direction in which a causal arrow points

6 6 When gathering data in the early stages of research When manipulating an independent variable is impossible or unethical When you are relating two or more naturally occurring variables

7 7 An independent variable is manipulated (with at least two levels) The value of the independent variable is determined by the researcher Manipulating an independent variable means exposing subjects to at least two values or levels of the variable The specific conditions associated with each level constitute the treatments of the experiment

8 8 A dependent variable is measured Also called a dependent measure Variable whose value you observe and measure in an experimental design The value of the dependent variable is determined by the subject’s behavior Hope to show a causal relationship between the values of the independent and dependent variables

9 9 The most basic experiment consists of an experimental and a control group Experimental group: Subjects receive experimental treatment Control group: Subjects do not receive experimental treatment Serves as baseline of behavior Control is exercised Holding them constant Randomizing their effects across treatments using random assignment over extraneous variables A causal relationship between the independent and dependent variables can be established

10 10 Strength Identification of causal relationships among variables Not possible with correlational research Limitations Can’t use experimental method if you cannot manipulate variables Tight control over extraneous variables limits generality of results Tradeoff exists between tight control and generality

11 11 INTERNAL VALIDITY is the degree to which your design tests what it was intended to test In an experiment, internal validity means showing that variation in the dependent variable is caused only by variation in the independent variable In correlational research, internal validity means that changes in the value of the criterion variable are solely related to changes in the value of the predictor variable Internal validity is threatened by CONFOUNDING and EXTRANEOUS VARIABLES Internal validity must be considered during the design phase of research

12 12 HistoryEvents may occur between multiple observations. MaturationParticipants may become older or fatigued. TestingTaking a pretest can affect results of a later test. InstrumentationChanges in instrument calibration or observers may change results. Statistical regression Subjects may be selected based on extreme scores. Biased subject selection Subjects may be chosen in a biased fashion. Experimental mortality Differential loss of subjects from groups in a study may occur.

13 13 EXTERNAL VALIDITY is the degree to which results generalize beyond your sample and research setting External validity is threatened by Using a highly controlled laboratory setting Using Restricted populations Using pretests Presence of demand characteristics and experimenter bias Subject selection bias

14 14 Steps taken to increase internal validity may decrease external validity and vice versa Internal validity may be more important in basic research External validity may be more important in applied research Issues relating to internal and external validity must be considered when designing a study

15 15 Reactive testingA pretest may affect reactions to an experimental variable. Interactions between selection biases and the independent variable Results may apply only to subjects representing a unique group. Reactive effects of experimental arrangements Artificial experimental manipulations or the subject’s knowledge that he or she is a research subject may affect results. Multiple treatment interference Exposure to early treatments may affect responses to later treatments.

16 16 The laboratory setting Affords greatest control over extraneous variables Higher levels of internal validity Lower levels of external validity Simulations Attempt to recreate the real world in the laboratory Realism is an issue Mundane realism: How well does a simulation mimic the real world event being simulated Experimental realism: How engaging is the simulation for participants

17 17 The field setting Study conducted in a real world environment Field experiment: Manipulate variables in the field High degree of external validity Internal validity may be low Difficult to control extraneous variables

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