Psych 311 Unit 10 Study guide

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1

Comparing Research Strategies: Purpose

  • Descriptive: To describe individual variables as they already exist within a specific group
  • Correlational: To describe the relationships between variables (does not attempt to explain)
  • Experimental: To explain a cause-and-effect relationship between (usually) two variables
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Comparing Research Strategies: Data

  • Descriptive: Measures variables of interest for every individual
  • Correlational: Measures two variables for each individual and relates them to each other
  • Experimental: Creates two treatment conditions by changing the level of one variable and measures 2nd variable for participants in each condition (and relates groups to each other)
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Experimental research: Steps

1. Manipulate the independent variable and observe dependent variable to see if there are changes

2. To establish cause-and-effect, rule out possibility that changes were caused by another variable

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Experimental research: key terms

  • Independent Variable: Manipulated variable; usually two or more treatment conditions
  • Dependent Variable: Variable observed for changes to assess affect of independent variable
  • Treatment Condition: A situation/environment characterized by one specific value of manipulated variable
  • Levels: Levels of the independent variable; specific conditions used in the experiment
  • Extraneous Variables: Variables other than independent or dependent that influence the relationship between study variables
  • Confounding Variables: Variables that that vary with the changing level of the independent variable
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Types of extraneous variables

  • Environmental Variables
  • Individual Differences
  • Time-Related Variables
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When is an extraneous variable confouding?

  • Confound
    • If it influences the DV
    • If it varies systematically with the IV
  • Not a Confound (Not a threat)
    • If no influence on DV, then no threat
    • Example: individuals in a memory experiment may wear different types of shoes (no threat)
    • A variable that changes randomly, without relation to IV is no threat
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Four elements of true experiments

card image
  • Manipulation: Researcher manipulates one variable (IV) by changing its value to create a set of two or more treatment conditions, unique to experimental research
  • Measurement: A second variable (DV) is measured for a group of participants to obtain a set of scores in each treatment condition.
  • Comparison: The scores in one treatment condition are compared with the scores in another treatment condition. Consistent differences are evidence that the manipulation caused changes.
  • Control: All other variables are controlled to be sure that they do not influence the two variables being examined, unique to experimental research
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Manipulation

  • Steps for Manipulation
    • Decide which values of independent variable that you would like to examine
    • Create a series of treatment conditions corresponding to those values
  • Purpose of Manipulation
    • To allow researchers to determine the direction of a relationship (crucial for experimental research)
  • Manipulation and Directionality
    • Manipulation allows researchers to observe directions of relationships
  • Manipulation and Third Variables
    • Manipulation helps researchers to control outside variables (instead of waiting for changes to naturally occur)
    • Manipulation reduces influence of third variables
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Manipulation check

  • Manipulation Check
    • An additional measure to assess how the participants perceived and interpreted the manipulation and/or to assess the direct effect of the manipulation
  • How to Conduct Manipulation Checks
    • Measure independent variable to ensure changes occurred
    • Ask participants about the manipulation in a questionnaire
10

Why is manipulation check important?

  • Participant Manipulations: When manipulation involves something within participant (such as frustration)
  • Subtle Manipulations: When variation is not salient and may not be noticed by participants
  • Simulations: When a study is simulating a real-world situation and the effectiveness depends on participants’ perception and acceptance
  • Placebo Controls: Placebos depend on credibility so manipulation check assesses realism of the placebo
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Measurement

A second variable is measured for a group of participants to obtain a set of scores in each treatment condition.

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Comparison

  • Experiment Group: Treatment group in an experiment
  • Control Group: refers to the no-treatment condition in an experiment
    • Two types: no-treatment controls and placebo controls
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Comparison groups

  • No-Treatment Control
    • Participants do not receive the treatment being evaluated
  • Placebo Control
    • Placebo – inert or innocuous medication that has no medicinal effect
    • Placebo Effect – a response by participant even though placebo has no effect on the body; person thinks medication is effective
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Control

  • Definition
    • Ensuring that the observed relationship is not contaminated by the influence of other variables
    • Eliminating all confounding variables
  • Purpose of Control
    • Experiments aim to show that the manipulated variable is responsible for observed changes
    • Purpose is to rule out any other possible explanations for observed changes
  • Control and Third Variables
    • Very important to control third variables that change along with the independent variable and can affect the dependent variable
    • Ways to Control Extraneous Variables
      • Holding
      • Matching (or counterbalancing)
      • Randomization
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Randomization

The use of a randomized process to avoid a systematic relationship between variables

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Random assignment

The use of random process to assign participants to treatment conditions

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Controlling extraneous variables

  • Holding: An extraneous variable can be eliminated by holding it constant or restricting it to a specific range
  • Matching: Values can be matched across conditions through matched assignment
  • Randomization: Use of random process to avoid systematic relationship between two variables
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Pro's and Con's of control methods

  • Holding
    • Requires extra effort
    • Used for 1 or 2 variables
    • Limits generalization (and external validity
  • Matching
    • Requires extra effort
    • Used for 1 or 2 variables
  • Randomizing
    • Can control a wide variety of variables simultaneously
    • Not guaranteed 100% successful (chance)
    • Most commonly used
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Elements of experimental research

  • Comparison: The scores in one treatment condition are compared with the scores in another treatment condition. Consistent differences are evidence that manipulation caused changes.
  • Control: All other variables are controlled to be sure that they do not influence the two variables being examined.
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External validity

  • External Validity: The extent to which research results can be generalized to people, settings, times, measures, and characteristics other than those used in the study
  • Threat to External Validity: Any characteristic of a study that limits the ability to generalize the study’s results
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Simulation

  • The creation of experimental conditions that simulate the natural environment where the behaviors being studied would naturally occur
  • PURPOSE: to test “real-world” conditions in a safe environment
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Types of simulation

  • Mundane Realism: Superficial, usually physical, characteristics of the simulation, which probably have little positive effect on external validity
  • Experimental Realism: Psychological aspects of the simulation, extent to which participants become immersed and behave normally, unmindful of the fact they are in an experiment
23

Field studies

  • Research conducted in a place that the participant perceives is a natural environment
  • PURPOSE: to test real life behavior in a natural environment
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Pro's and Con's of simulation and field studies

  • Simulation
    • PRO: Allows researchers to study life-like situations
    • CON: Researcher loses control and risks threats to internal validity – study relies on participant acceptance of simulation
  • Field Studies
    • PRO: Allows researchers to study life-like situations
    • CON: Researcher loses control and risks threats to internal validity – unpredictable participants