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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 threats to experimental validity To examine some basic quasi-experimental designs. Type of general approaches to design. Descriptive

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## Lecture 8: Quasi-experiments

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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 threats to experimental validity • To examine some basic quasi-experimental designs**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**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**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**Statistical validity**• Risk of making a type 1 error • Power • Fishing • Reliability of measures, treatments • Random irrelevance • Random heterogeneity of respondents**External validity:generalisation**• Is the effect stable • Over time • Across individuals • Across IVs & DVs • Across places**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**Construct validity**• Experimenter effects • Structural • Mono-operation bias • Mono-method bias • Poor explication of constructs • Interpersonal • Demand characteristics • Apprehension evaluation • Rosenthal effect**Quasi-experiments**Nomenclature X = a treatment O = Observation … = Not randomly assigned**Uninterrupted designs**One group pre- post test design O X O Threats = history, maturation regression**Non-equivalent groups**Untreated control group with pre and post test O X O ………… O O**Reverse treatments**O X+ O ……………. O x- O**ITSDs**OOOOXOOOO ……………….. OOOO OOOO OO OOOXOOO OOXOOO OOO Withswitch replication**ARIMA**• OOOXOOO • 456 Upward drift • 444 Upward constant • 466 Gradual upwards • 333 333 No change**Regression discontinuity**Depression Poverty Short Long**Randomized field trials**• Randomisation by independent group • Make seek treatment elsewhere • Within condition effects • Placebo-control**Experiments: the last word**• Experiments are important because they allow us to show what can or ought to happen • Bio feedback • Milgram • Sherrif’s boys camp study

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