© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Chapter 4 Choosing a Research Design.

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© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Chapter 4 Choosing a Research Design

© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Functions of Research Design Two Major Activities Exploratory Classifying Behavior Identifying Important Variables Identifying Relation Between Variables and the Behavior. Hypothesis Testing Consists of Evaluating potential explanations for the observed relationships. Exploratory provides the data to develop explanations

© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Relationship Catagories Two broad catagories of relationships between variables and behavior are: Causal One variable directly or indirectly influences another. May be unidirectional or bidirectional. Correlational Changes in one variable accompany changes in another (a relationship exists). Covary- When one variable is associated with specific changes in another.

© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Correlational Research: Major Features 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 (indep) can be used to predict the value of a CRITERION VARIABLE (depend)

© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Correlational Research: Major Features Correlational research cannot be used to establish causal relationships among variables THIRD VARIABLE PROBLEM The possibility that correlational relationships may result from the action of an unobserved variable. DIRECTIONALITY PROBLEM The difficulty of knowing the direction of causality between two variables.

© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Correlational Research: When Is It Used? When gathering data in the early stages of research When manipulating an independent variable is impossible or unethical e.g. abuse When you are relating two or more naturally occurring variables e.g. college success

© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Experimental Research: Major Features An independent variable is manipulated (with at least two levels) Treatment (conditions associated with each level of the variable) A dependent variable is measured The most basic experiment consists of an experimental and a control group Control is exercised over extraneous variables either by holding them constant or by randomizing their effects across treatments A causal relationship between the independent and dependent variables can be established

© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Extraneous variables Variables that may affect the behavior being investigated but are not of interest in the study. If not controlled 1) difficult to detect effects of independent variable & 2) chance differences may be produced. Two Controls Hold them constant (assure all variables are kept at same level besides independent) Randomize their effects across treatments (random assignment helps)

© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Strength and Limitations of Experimental Research 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

© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Internal Validity 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

© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. External Validity EXTERNAL VALIDITY is the degree to which results generalize beyond your sample and research setting External validity is threatened by the use of a highly controlled laboratory setting, restricted populations, pretests, demand characteristics, experimenter bias, and subject selection bias Steps taken to increase internal validity may decrease external validity and vice versa Internal validity may be more important in basic research; external validity, in applied research

© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Factors Affecting Internal Validity 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.

© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Factors Affecting External Validity 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.

© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Research Settings The laboratory setting Affords greatest control over extraneous variables 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 The field setting Study conducted in a real world environment Field experiment: Manipulate variables in the field High degree of external validity, but internal validity may be low