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More Research Basics

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Title: More Research Basics


1
More Research Basics
  • Descriptive Research
  • Sampling
  • Measurement

2
Descriptive Research
  • Naturalistic Observation
  • Observation and recording of naturally occurring
    behavior
  • Often must limit the behaviors of interest
  • Interobserver reliability
  • Degree to which multiple observers agree about
    the behavior they observed

3
Descriptive Research
  • Case Studies
  • Intensive observation of one person or a small
    group of people for an extended period of time

4
Descriptive Research
  • Meta-Analysis
  • Study of existing research
  • Method of statistically combining the results of
    many studies on the same topic

5
Descriptive Research
  • Survey Research
  • Want to know about attitudes, beliefs, behaviors,
    thoughts? Just ask
  • Must have adequate sample to answer the questions
    youre asking
  • Representative of the population you want to
    generalize to

6
Sampling
  • Generalization
  • The degree to which the conclusions in your study
    would hold for other persons in other places and
    at other times

7
Sampling
8
Sampling
  • Random Sampling Techniques
  • Simple random sampling
  • Stratified random sampling
  • Systematic random sampling
  • Cluster sampling
  • Multistage sampling

9
Sampling
  • Nonrandom Sampling Techniques
  • Accidental Sampling
  • Convenience Sampling
  • Expert Sampling
  • Quota Sampling
  • Heterogeneity Sampling
  • Snowball Sampling

10
Measurement
  • The process of observing and recording the
    observations that are collected as part of a
    research effort

11
Measurement
  • Construct Validity The approximate truth of the
    conclusion that your operationalization
    accurately reflects its constructs.
  • Central questions to ask are
  • Is your operationalization an accurate
    translation of the construct?
  • Does your program/treatment accurately reflect
    what you intended?
  • Does your sample accurately represent your idea
    of the population of interest?
  • Are you measuring what you intended to measure?

12
The Idea of Construct Validity
13
Measurement Validity Types
  • Construct Validity
  • Translation Validity
  • Face Validity
  • Content Validity
  • Criterion-related Validity
  • Predictive Validity
  • Concurrent Validity
  • Convergent Validity
  • Discriminant Validity

14
Translation Validity
  • Focuses on whether the operationalization (i.e.,
    measure) is a good translation of the construct
  • Face Validity On its face, does the
    operationalization look like a good translation
    of the construct?
  • Weakest way to demonstrate construct validity
  • Improved with expert judgment

15
Translation Validity
  • Focuses on whether the operationalization (i.e.,
    measure) is a good translation of the construct
  • Content Validity Operationalization is checked
    against the relevant content domain for the
    construct
  • May be difficult to determine all of the
    characteristics that constitute the domain
  • A systematic check of the operationalization
    against the content domain increases rigor

16
Criterion-related Validity
  • The performance of your operationalization (i.e.,
    measure) is checked against some criterion
  • A prediction of how the operationalization will
    perform on some other measure based on your
    theory or construct
  • Validating a measure based on its relationship to
    another independent measure

17
Criterion-related Validity
  • Predictive Validity Operationalizations
    ability to predict something it should
    theoretically be able to predict
  • Demonstrated by a high correlation between your
    measure and the criterion measure
  • Is SAT score able to predict success in college
    (i.e., college GPA)?

18
Criterion-related Validity
  • Concurrent Validity Operationalizations ability
    to distinguish between groups it should
    theoretically be able to distinguish between
  • Results are more powerful if your measure is able
    to distinguish between two similar groups
  • Can a measure of empowerment distinguish between
    supervisors and employees?

19
Criterion-related Validity
  • Convergent Validity Degree to which the
    operationalization is similar to (converges on)
    other operationalizations to which it
    theoretically should be similar
  • Demonstrated by high correlation of your measure
    with another measure of the same construct
  • Does your measure of depression correlate highly
    with another measure of depression?

20
Criterion-related Validity
  • Discriminant Validity Degree to which the
    operationalization is not similar to (diverges
    from) other operationalizations to which it
    theoretically should not be similar
  • Demonstrated by low correlation of your measure
    with a measure of a theoretically opposite (or
    dissimilar) construct
  • Is there a low correlation between your measure
    of depression and a measure of well-being?

21
Convergent and Discriminant Validity Correlations
22
Threats to Construct Validity
  • Inadequate preoperational explication of
    constructs
  • Mono-operation bias
  • Mono-method bias
  • Interaction of different treatments
  • Interaction of testing and treatment
  • Restricted generalizability across constructs
  • Confounding constructs and levels of constructs
  • Social threats to construct validity

23
Levels of Measurement
  • The relationship among the values that are
    assigned to the attributes for a variable
  • Determines what statistical analyses are
    appropriate
  • Levels
  • Nominal
  • Ordinal
  • Interval
  • Ratio

24
Levels of Measurement
  • Nominal Numerical values simply name the
    attribute
  • No ordering of values is implied
  • Numerical values are simply short codes for
    longer names
  • Color of your car
  • 1 red
  • 2 yellow
  • 3 black

25
Levels of Measurement
  • Ordinal Attributes can be rank ordered
  • Distances/intervals between attributes have no
    meaning
  • Degree of satisfaction
  • 1 dissatisfied
  • 2 neutral
  • 3 satisfied

26
Levels of Measurement
  • Interval Distances/intervals between attributes
    do have meaning
  • Temperature on a Fahrenheit scale
  • Ratios do not make sense
  • 80 degrees is not twice as hot as 40 degrees
  • Not meaningful, absolute zero
  • Zero degrees (F) is not the absence of temperature

27
Levels of Measurement
  • Ratio Always a meaningful, absolute zero
  • Allows construction of meaningful ratios
  • Weight
  • Zero pounds is the absence of weight
  • 80 pounds is twice as much weight as 40 pounds

28
Levels of Measurement
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