Final Study Guide Research Design

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Final Study GuideResearch Design
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Experimental Research
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Experimental Research

• Researchers manipulate independent variable - 2
  levels
• And measure the other (dependent variable)
• Give treatment to participants and observe if it
  causes changes in behavior
• Compare experimental group (w/ treatment) with a
  control group (no treatment)
• Can say IV caused change in the DV

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Independent Variable

• The variable whose impact you want to know
• Stimulus Input Variable
• The variable you manipulate in experimental
  research

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Dependent Variable

• The variable whose changes you want to know
• You measure it
• Outcome Response variable

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• Random Selection
• A way to choose your sample of study
• Any member of population has equal chance of
  being selected
• Random Assignment
• A way to assign participants in sample to the
  various treatment conditions (groups will receive
  different level of IV)
• Any member of your sample has equal chance of
  being assigned in any treatment group

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Internal Validity

• Ability of your research design to adequately
  test your hypothesis
• Showing that variation in I.V. CAUSED the
  variation in the D.V. in experiment
• In correlational study,
• Showing that changes in value of criterion
  variable relate solely to changes in value of
  predictor variable

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Confounding

• Whenever 2 or more variables combine in a way
  that their effects cannot be separated
  confounding.
• Thus, the teaching method study as designed lacks
  internal validity.
• You dont know if the change in the DV is from
  the IV or from confounding variable

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Quasi-experimental research

• Naturally occurring conditions
• (IV change)
• No control over variables influencing behavior
  (confounding variables)
• Another variable that changed along with the
  variable of interest may have caused the observed
  effect
• (NO random assignment)

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Non-Experimental Research
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Non-experimental Correlational research

• Determine whether 2 or more variables are
  associated,
• If so, to establish direction and strength of
  relationships
• Observe variables as they are,
• cant manipulate them

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Research design

• Manipulate IV
  Random Assignment
• Experimental (Causal) x x
• Quasi-experimental x
• Non-experimental /
• Correlational
• Predictive
• Descriptive

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• Causal - (Experimental)
• one variable directly or indirectly influences
  another.
• Correlational - (Non-experimental)
• Changes in one variable accompany changes in
  another.
• A relationship exists. Dont know if either
  variable actually influences the other.

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TERMS

• Population
• Universe/entire set of people you want to draw
  conclusions about
• Sample
• Subset of the population
• People actually in your study
• Sampling error
• Differences between sample population

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Sampling

• Drawing a subgroup from a population (vs. Census)

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Probability vs. Non-probability
Probability Sampling
Non-probability Sampling

• Simple random
• Systematic random
• Stratified random
• Cluster

• Convenience
• Snowball
• Quota
• Purposive

Population info Available
Population info Not available
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Representativenss Generalizability

• Representativeness Resemblance to the
  population characteristics
• Generalizability An ability to generalize the
  results of your study to the whole population
• High representativeness High generalizability
• Probability sampling allows higher
  representativeness than non-probability

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External Validity

• Degree that results can be extended beyond the
  limited research setting
• Generalizable
• Based on sample ( rats, college students, whites,
  males, lab setting)

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Non-Probability Sampling
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Convenience Sampling

• Get available people in the population
• Low representativeness / generalizability

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Quota Sampling

• Predetermine the proportion of groups in the
  sample (e.g., male 50, female 50)

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Conceptualization Operationalization
Idea
Clarification
Conceptualization
Operationalization
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Operationalization

• From complex variable to series of simpler
  variables
• Redefining a variable in terms of steps to
  measure
• Conceptual definition ? Operational definition
• What the researcher must do to MEASURE it

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Types of Measurement Validity
Empirical (Criterion-related)
Judgmental

• Face validity
• Content validity

• Predictive
• Concurrent
• Convergent
• Discriminant

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O T E rule
Observed score True score Eerror
Observed measured score, result True true,
actual, exact state Error measurement error
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Reliability of a Measure

• Degree to which a measure (score, observation) is
  affected by error
• A reliable measure has little or no error

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Types of Reliability

• Interobserver (interrater) reliability
• Test-Retest reliability
• Parallel-forms reliability
• Split- half

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Inter-rater Agreement

• Consistency between measurements by two or more
  observers
• Different observers watch the same sample of
  behavior
• Compute proportion of time both observers
  recorded the same behavior as happening

agreements agreements
disagreements ( of observations)

• Training needed for observers

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Increasing reliability

• Increase number of items on your questionnaire
  (no 1 or 2 item measures)
• Write clear, well-written items on survey
• Standardize administration procedures
• Treat all participants alike
• Timing, procedures, instructions alike

• Score survey carefully -- avoid errors

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Valid and Reliable

• A good measurement
• Measures what it should measure in a consistent
  way

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Reliable but Invalid

• Your measurement is consistent, but not measuring
  what it is supposed to measure

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Research Report Structure

• Abstract
• Introduction
• Method
• Results
• Discussion
• Reference