Presentation on theme: "Soc Week 3 Causation and Experiments"— Presentation transcript:
1 Soc. 2155 Week 3 Causation and Experiments I. CausationRelationships between variablesTypes of associationCriteria for causalityII. Experiments – testing cause and effectExplanatory researchTrue experimental designsQuasi-experimental designsInternal validityExternal validityEthical issuesStrengths and weaknesses
2 Association = relationship Does not have to be causal.Positive association = as X increases, Y increases.Negative association = as X increases, Y decreases.Qualitative variables: presence of X predicts presence or absence of Y.
3 Which associations could be causal? Years work experience/ income# churches / # bars in a townCigarette smoking/ lung cancer# firefighters called to fire/ $ amount of damageRace/ povertySpurious association = apparent association caused by a third factor
4 Cause = necessary and sufficient condition Necessary: X must be present in order for Y to follow.(ex: to get an “A” it is necessary to complete all assignments).Sufficient: If X occurs, Y must follow.(ex: if you get 100% on every assignment, you will get an “A” in the class.)
5 3 criteria for causality X causes Y if: X precedes Y in timeX and Y are statistically associatedAll other potential causes of Y have been ruled out.
6 Additional CriteriaMechanism – connection between “cause” and “effect” – how the cause operates to produce the effect.Context – situations, groups, places, conditions, etc. In which the cause produces the effect.
7 Determinants/ partial causes Most sociological phenomena have multiple causes. “Determinant” = partial cause or predictor. Not a complete cause.Example: Some determinants of income:Marital statusTalentPersonalityJob dutiesType of companyEducationSkillTrainingExperienceIntelligenceOccupationGenderRaceGeographic areaIndustry
8 Types of CausesNomothetic Cause – General explanation of a class of phenomena. (e.g., causes of terrorism, crime)Idiographic Cause – Specific event or sequence of events. (e.g., causes of 9/11 attacks, sudden rise in crime rates) May be historical in focus.
9 Multivariate Relationships XZXZYYZ intervenes B/T X and Y OR Z “explains” relationship B/T X and YZ as spurious cause of X and YZXXYYZDirect and indirect effectsMultiple causes (determinants) of Y
10 Experiments Explanatory research True experiments Experimental designs Quasi-experimental designsInternal validityExternal validityEthical issuesStrengths and weaknesses
11 Explanatory Research Purpose: to explain, to determine cause/effect What is explained?Variation in the dependent variableWhat can be studied in an experiment?Limited, narrow causal relationshipsVariables that can be studied in labTopics for which theory has been developed
12 True experiment includes Two groups (experimental and control)Random assignment to groupsVariation in independent variable (manipulated by researcher)Measurement of dependent variable
13 The groupsExperimental group – is exposed to independent variable (I.V.)Control group - is not exposed to I.V.I.V. is the only difference between the groupsAny differences in dependent variable (D.V.) must be due to I.V.
14 Assignment to groups Randomization Easy to carry out Can control for unmeasured or uncontrolled factorsMatchingSpecific characteristics matched in both groupsMay be very preciseRequires knowledge of relevant characteristicsMay not control for omitted factors
15 Pretesting Measures D.V. before experiment Establishes comparability of experimental and control groupsProvides baseline for comparison with posttestMay teach or “clue in” subjects (pretest effect)Costs extra
17 Experimental Designs Posttest-Only Effect of I.V. = (O1-O2) GroupsPretestI.V.Uncontrolled factorsPosttestChangeExper.N/AXO1ControlO2Effect of I.V. = (O1-O2)Eliminates effect of pretest
18 Experimental Designs Solomon four-group GroupsPretestI.V.Uncontrolled factorsPosttestChangeExper. 1O1XO3O3-O1Control 1O2O4O4-O2Exper. 2O5Control 2O6Effect of I.V. = (O3-O1) – (O4-O2) or (O5-O6)Effect of pretest = (O3-O5) or (O4-O6)
19 Quasi-Experimental Designs May be used when true experiment isn’t possibleUsually involve fewer controlsNo control groupApproximately equivalent control groupMay take place in the fieldMay be “ex post facto:” designed after the “treatment”
20 Internal Validity Source of Invalidity Solution History – outside eventsControl groupMaturation – changes in subjectsTesting – subject may learnInstrumentation - measurementStatistical regression - moderationSelection bias- groups not comparableRandomizationMortality – dropping outContamination (competition, demoralization)Treatment misidentification (experimenter expectations, placebo effect, Hawthorne effect)Randomization, double blind, process analysis
21 External Validity Generalization to “real world” Often a problem in experiments2 main issuesWould sample subjects behave same way outside lab?Cross-population generalizability: would findings hold for different groups, times, places?
22 Ethical IssuesDeception (misleading subjects about purpose of experiment)Selective distribution of benefits (also risks, harm)
23 Experiments’ Strengths and Weaknesses Isolation of cause/effectHigh internal validityEasy to replicateBest used for explanatory studies (testing of hypotheses)WeaknessesExternal validity may be low or undeterminedEthical issuesHigh cost per subject