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Lecture 8: Quasi-experiments Aims & Objectives –To differentiate between true and quasi-experiments –To discuss the nature of random allocation –To examine.

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Presentation on theme: "Lecture 8: Quasi-experiments Aims & Objectives –To differentiate between true and quasi-experiments –To discuss the nature of random allocation –To examine."— Presentation transcript:

1 Lecture 8: Quasi-experiments Aims & Objectives –To differentiate between true and quasi-experiments –To discuss the nature of random allocation –To examine threats to experimental validity –To examine some basic quasi-experimental designs

2 Type of general approaches to design Descriptive What, where, when and to whom Relational Co-variaton Experimental Causal analysis via random allocation Quasi-experimental Causal statements when groups are not equivalent – no random allocation

3 Random allocation Every potential subject has an equal chance of being in any condition Simple randomisation Block randomisation –Blocks A&B, produce sequences e.g., AABB, ABAB. Sequences are selected at random and subjects selected at random into that block Stratified randomisation –Select on a characteristic that influences the groups and have block randomisation lists within those blocks

4 Internal validity: I Ruling out a third cause –Randomisation controls for History effects Maturation effects Mortality Statistical regression to the mean –Randomisation does not control for Effects equalising groups –Diffusion of treatment effects –Compensatory rivalry –Compensatory equalisation Effect separating groups –Resentful demoralisation

5 Statistical validity Risk of making a type 1 error –Power –Fishing –Reliability of measures, treatments –Random irrelevance –Random heterogeneity of respondents

6 External validity:generalisation Is the effect stable –Over time –Across individuals –Across IVs & DVs –Across places

7 Mook Research is not always about generalizability of findings Conceptualisation of generalizability are base don an agricultural model Experiments are about generalizability of theory not findings

8 Construct validity Experimenter effects –Structural Mono-operation bias Mono-method bias Poor explication of constructs –Interpersonal Demand characteristics Apprehension evaluation Rosenthal effect

9 Quasi-experiments Nomenclature X = a treatment O = Observation … = Not randomly assigned

10 Uninterrupted designs OXOOXO One group pre- post test design Threats = history, maturation regression

11 Non-equivalent groups OXO …………O Untreated control group with pre and post test

12 Reverse treatments OX+O ……………. Ox-O

13 ITSDs OOOOXOOOO ……………….. OOOO OO OOOXOOO OOXOOO OOO With switch replication

14 ARIMA OOOXOOO Upward drift Upward constant Gradual upwards No change

15 Regression discontinuity Depression ShortLong Poverty

16 Randomized field trials Randomisation by independent group Make seek treatment elsewhere –Within condition effects Placebo-control

17 Experiments: the last word Experiments are important because they allow us to show what can or ought to happen –Bio feedback –Milgram –Sherrifs boys camp study


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