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Experimental Methods 8. (Validity in Experiments (Test Validity (Content…

- - - - Research Design
        
        3 main
        Design Approaches:
        
        Statistical Control
        
        Descriptive Design (Describe)
        
        Correlation Design (Describe, Relation and Predict)
        
        Experimental Control
        
        Experimental Design
        
        Explain Causes
        
        Explain Effects
        
        find Cause-Effect Relations
        
        Relations
        
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        Cause
        
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        Effect
        
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      - Science
        
        Goals:
        
        Describe
        
        Predict
        
        find Causes
        
        Explain and Understand
- - - - Goal
        
        Increase Reliability
      - Each Observation (X) is a Sum of:
        True Score (T) +
        a Measurement Error (e)
        
        True Score (T)
        
        Measurement Error (e)
        
        Systematic E.
        
        Ex.:
        
        Social Desirability, Demand Characteristics,
        Unclear (/Bad) content, Experimenter Bias,
        Lying, Motivation
        
        Affects Validity
        
        we are Not Sure that
        we have Measured what we Intended to Measure
        
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        Unsystematic
        (Random) E.
        
        Ex.:
        
        daily shape, Situational conditions (noise in the room...),
        error by test administrators, memory
        
        Affects Reliability
        
        you do Not get the
        Precise Scores you wanted
        
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        Reliability Testing #
        
        allows to Discover Unsystematic Errors,
        
        while Systematic E. are Camouflaged
        as a part of the True Score
        
        can be Calculated Out:
        
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        Systematic and Unsystematic Variation
        in Experiments
        
        Casual Unsystematic Variance
        
        all the Variation Not due to
        our Manipulation
        
        we hope is due to
        Unsystematic Variation
        
        and not due Confounding Variable
        
        Systematic Variation
        
        we have Control on Variation
        
        we Intervene in the Experiment
        by Manipulating a Variable
        
        the Variation is due to the Manipulation
        
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- - - - Formal
        
        Introducing an Event (Indipendent Var.) in a Controlled Environment,
        to Measure the Effect of the Variable on Other Variables
        
        Scientific Method used to
        Test Hypotheses of Cause and Effcet
        
        Control Group
        
        Randomized Participants
        
        Each Participant has the
        same Chance to be Selected
        
        No Bias in Selection
        
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        can Talk bt Causal Relations
        
        when a Participant that receives the Manipulation
        can be Switched w Another Participant
        and we get the Same Results
    - - Between-Subject
        
        (At least) 1 Experimental Group
        and 1 Control Group
      - Within Subjects
        
        the Same Group is Measured Before and After the Manipulation
      - N=1 Design
        
        1 Individual is followed Over Time
      - Quasi-Experimental
        
        Same as Experimental Design,
        but Lacks Randomized Assignment of Participants
    - - Sample: Representative
        
        Control and Experimental Groups
        
        Indipendent Variable
        
        Dependent Variable
        
        External Conditions: control over External
        Variables that may Possibly have an Effect on Y
- - - - External
        Validity
        
        if the Findings are Generalizable
        (to the Real World)
        
        External to the Controlled Environment
        
        Ex. in the study of the tapis roulant
        
        whether the findings (the relation between the ind. variable of seeing the progress on a display and the dep. var. of increased running) apply to other contexts, like the impotance of measurement in systematic goal setting
        
        Threats
        
        Observation Effects /
        Reactivity
        
        Experimenter Bias
        
        Hawthorne Effect
        
        etc.
        
        Internal
        Validity
        
        Threats
        
        Between-Subjects Exp.
        
        Selection Bias
        
        there are Systematic Diffrences
        btw the Experimental and Control Groups
        Before the Manipulation
        
        Diffusion of
        Indipendent Variable
        
        the Effect of the Manipulation is Carried Over
        to the Control Group
        
        Selective Drop-Out Rate
        
        Within Subjects Exp.
        
        Carry Over
        Effect
        
        Previous Measurements
        have a Transissible Effect
        
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        how to Tackle them
        
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        History
        
        Changes in the Circumstances
        that are not due to Changes in X
        
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        Changes in the Features
        of the Measuring Instruments
        
        Statistical Regression
        
        Scores, especially Extreme ones,
        have a Tendency to move toward the Average
        (in the next Measurement)
        
        Maturing
        
        Natural Changes in the Person
        during the Time Interval
        
        Definition
        
        Formal
        
        whether Researchers have Drawn the Correct Conclusions on the Conditions of Cause-Effect in the Experiment
        
        Inferences have Internal Validity if a Causal Relation btw 2 Variables is Demonstrated
        
        the extent to which a Causal Conclusion based on a study is Warranted, which is determined by the degree to which a study Minimizes Systematic Error (or 'Bias')
        
        the Cause Precedes the Effect
        
        the Cause and the Effect are Related (Covariation)
        
        there are No Plausible Alternative Explanations for the Observed Covariation (Nonspuriousness)
        
        Personal
        
        when we Control all Extraneous Variables and the Only Variable Influencing the Results is the One being Manipulated (Indipendent V.)
        and Not other Extraneous Variables
        
        the Degree to which the Experiment supports Clear Causal Conclusions
        
        Ex. In the study of ppl. running more on the tapis roulant when seeing their progress on the diplay
        
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  - - - Concerns:
        
        Samping
        
        Analyis Method
        
        Number Precision
        
        Representativity
        
        etc.