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Literature Review Paper Use a summary narrative form Assignment sheet Outline format essential.

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Presentation on theme: "Literature Review Paper Use a summary narrative form Assignment sheet Outline format essential."— Presentation transcript:

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2 Literature Review Paper Use a summary narrative form Assignment sheet http://commfaculty.fullerton.edu/jreinard/sample_papers.htm Outline format essential

3 Agenda for This Unit Experimental Design Causal Reasoning in Experiments Notation Factorial Designs Main Effects Interaction Effects

4 Experimental Design Defined: a study of the effects of variables manipulated by a researcher in a situation in which all other variables are controlled, completed for the purpose of establishing causal relationships

5 Experimental Design Distinguishing Carefully Designed Studies from Experiments Manipulation of Variables Cause-effect Conclusions

6 Finding True Causes in Experiments The Challenge of Control A Case Study

7 Notation O - observation X - experimental variable R - randomization

8 Designs Reading Designs Pre-Experimental vs. True Experimental Designs

9 Randomization controlling for extraneous variables random assignment random selection

10 Comparing Designs

11 Internal Validity Defined: the degree to which the researcher can make an unequivocal statement of experimental effect Sources Mnemonic device: He said my tush is sagging extra inches.

12 External Validity Defined: the degree to which research findings can be generalized to other similar circumstances Sources

13 Other Sources of Invalidity Law of the Instrument Experimenter Effects (Demand Characteristics) Ignoring Initial Differences between Control and Experimental Groups

14 Factorial Designs Defined: experimental designs using more than one independent variable

15 One Factor Designs X1X1 - +

16 A Two Factor Design A 2 x 2 Design X1X1 - + - + X2X2

17 A 3 x 2 Design X1X1 - + X2X2 LOWMO HI

18 A Three Factor Design X1X1 - + - + X2X2 - + X3X3

19 The Relationship Between Factorial and Simple Designs X1X1 - + - + X2X2

20 X1X1 - + - + X2X2 R X O R O R X O R O R X O R O R X O R O

21 Identification of Offset Control Groups X1X1 - + - + X2X2 R X O R O R X O R O R X O R O R X O R O

22 Identification of Offset Control Groups X1X1 - + - + X2X2 R X O R O R X O R O R X O R O

23 Designs in Which Control Groups are Included X1X1 - + - + X2X2 R X O R O R X O R O R X O R O

24 Main Effects Defined: dependent variable effects from independent variables separately

25 A Main Effect Example X1X1 - + - + X2X2 50 40 30 20 Amount of Attitude Change Advocated Source Character

26 A Main Effect Example X1X1 - + - + X2X2 50 40 30 20 30 40 Amount of Attitude Change Advocated Source Character

27 A Main Effect Example X1X1 - + - + X2X2 50 40 30 20 25 45 30 40 Amount of Attitude Change Advocated Source Character

28 Diagrams of Main Effects 20 15 10 5 Men Women Variable 1 D.V.: touching

29 Diagrams of Main Effects 20 15 10 5 Men Women Variable 1 D.V.: touching

30 Diagrams of Main Effects 50 40 30 20 Low High Variable 1 Amount of Attitude Change Advocated D.V.: Attitude Change

31 Diagrams of Main Effects 50 40 30 20 Low High Variable 1 Variable 2 (Low) Amount of Attitude Change Advocated Source Character D.V.: Attitude Change

32 Diagrams of Main Effects 50 40 30 20 Low High Variable 1 Variable 2 (High) Variable 2 (Low) Amount of Attitude Change Advocated Source Character D.V.: Attitude Change

33 Effects X1X1 - + - + X2X2 19 9 21 11

34 Effects X1X1 - + - + X2X2 19 9 21 11 16 14

35 Effects X1X1 - + - + X2X2 19 9 21 11 16 14 20 10

36 Diagrams of Main Effects 20 15 10 5 Low High Variable 1

37 Diagrams of Main Effects 20 15 10 5 Low High Variable 1 Variable 2 (Low)

38 Diagrams of Main Effects 20 15 10 5 Low High Variable 1 Variable 2 (Low) Variable 2 (High)

39 Interaction Effects Defined: dependent variable effects from independent variables taken together Forms: Ordinal (in the same direction as the main effects of variables involved) Disordinal (not in the same direction as the main effects of the variables involved)

40 An Interaction Effect Example X1X1 - + - + X2X2 50 20

41 An Interaction Effect Example X1X1 - + - + X2X2 50 20 35

42 An Interaction Effect Example X1X1 - + - + X2X2 50 20 35 20 35

43 Diagram of the Interaction Effect 50 40 30 20 Low High Variable 1

44 Diagram of the Interaction Effect 50 40 30 20 Low High Variable 1 Variable 2 (Low)

45 Diagram of the Interaction Effect 50 40 30 20 Low High Variable 1 Variable 2 (High) Variable 2 (Low)

46 Another Interaction Effect Example X1X1 - + - + X2X2 20 40 20 Sex of Clinician Male Female Type of Stuttering: Clonic Blocking

47 Another Interaction Effect Example X1X1 - + - + X2X2 20 40 20 Sex of Clinician Male Female Type of Stuttering: Clonic Blocking 30

48 Another Interaction Effect Example X1X1 - + - + X2X2 20 40 20 Sex of Clinician Male Female Type of Stuttering: Clonic Blocking 30

49 Diagram of the Interaction Effect 40 30 20 10 Low High Variable 1 Male Female Sex of Clinician

50 Diagram of the Interaction Effect 40 30 20 10 Low High Variable 1 Variable 2 (Low) Male Female Sex of Clinician Type of Stuttering: Clonic

51 Diagram of the Interaction Effect 40 30 20 10 Low High Variable 1 Variable 2 (Low) Variable 2 (High) Male Female Sex of Clinician Type of Stuttering: Clonic Blocking

52 Interpreting Ordinal Interactions acceptable to look at the independent variables separately permissible to interpret main effects for independent variables involved in the interaction

53 Interpreting Disordinal Interactions must look at both independent variables together not permissible to interpret main effects for independent variables involved in the interaction

54 OK to Interpret Main Effects 50 40 30 20 Low High Variable 1 Variable 2 (High) Variable 2 (Low)

55 Not OK to Interpret Main Effects 40 30 20 10 Low High Variable 1 Variable 2 (Low) Variable 2 (High)

56 Effects: Example 1 20 15 10 5 Low High Variable 2

57 Effects: Example 1 20 15 10 5 Low High Variable 2 Variable 1 (Low)

58 Effects: Example 1 20 15 10 5 Low High Variable 2 Variable 1(High) Variable 1 (Low)

59 20 15 10 5 Low High Variable 2 Effects: Example 2

60 20 15 10 5 Low High Variable 2 Effects: Example 2 Variable 1 (Low)

61 20 15 10 5 Low High Variable 2 Effects: Example 2 Variable 1 (High) Variable 1 (Low)


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