Beginning the Research Design
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Transcript of Beginning the Research Design
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Beginning the Research DesignTheory, Questions, Hypotheses
Designing Tests for the above:Conceptualization,
Operationalization, and Measurement
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Conceptualization Process of specifying what we mean
when we use particular terms. Produces an agreed upon meaning
for a concept for the purposes of research.
Describes the indicators we'll use to measure the concept and the different aspects of the concept.
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From Concept to Measurement Progression from what a term
means to measurement in a scientific study: Conceptualization Nominal Definition Operational Definition Measurements in the Real World
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Four Levels of Measurement1. Nominal - offer names for labels
for characteristics (gender, birthplace).
2. Ordinal - variables with attributes we can logically rank and order.
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Four Levels of Measurement3. Interval - distances separating
variables (temperature scale).4. Ratio - attributes composing a
variable are based on a true zero point (age).
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MeasurementsThings Scientists Measure Direct observables - things that can
be observed simply and directly. Indirect observables - things that
require more subtle observations. Constructs - based on observations
that cannot be observed.
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Measurement Quality
Reliability Validity
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ReliablityGENERAL DEFINITION:Accuracy or precision of a measuring instrument. SPECIFIC DEFINITIONS:
1. Similar results - stability, dependability predictability
2. Accuracy – consistency
3. Absence of random or chance error -- extent to which errors of measurement are present in a measuring instrument
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Tests for Checking Reliability
Test-retest method - take the same measurement more than once.
Equivalence: use "essentially the same" measurement items on the same instrument or on different instruments and compare the answers (same time period). Split-half, Random half, alternate forms. Use established measures.
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Internal ValidityDEFINITION: the ability of the measuring instrument to
measure one's theoretical concepts.
METHODS OF ASSESSING VALIDITY:
PRAGMATIC (or Criterion) VALIDITY: predict to an outside criterion and compare the outcome to the outside criterion
a. Concurrent: comparison to an existing or current outside criterionb. Predictive: comparison to a future outside criterion
FACE VALIDITY: obvious and self-evident content
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Validity (cont.)CONTENT VALIDITY: representativeness of
what is being measured to the intended concepts (capturing all the dimensions of the social concept)
CONSTRUCT VALIDITY: adequacy of the
measuring instrument for measuring the theoretical concepts and relationships; also adequacy of the logical structure of the conceptualization and operationalization.
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Construct Validity
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External Validity
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Political Polls and Survey Sampling In the 2000 Presidential election,
pollsters came within a couple of percentage points of estimating the votes of 100 million people.
To gather this information, they interviewed fewer than 2,000 people.
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Election Eve Polls - U.S. Presidential Candidates, 2000
Date Agency Gore Bush Nader
Buchanan
11/6 IDB/CSM 47 49 4 011/6 CBS 48 47 4 111/6 CNN/USA
Today] 46 48 4 1
11/6 Reuters/MSNBC
48 46 5 1
11/6 Voter.com
45 51 4 0
11/7 Results 48 48 3 1
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Observation and Sampling Polls and other forms of social research,
rest on observations. The task of researchers is to select the
key aspects to observe, or sample. Generalizing from a sample to a larger
population is called probability sampling and involves random selection.
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Types of Nonprobability Sampling Reliance on available subjects:
• Only justified if less risky sampling methods are not possible.
• Researchers must exercise caution in generalizing from their data when this method is used.
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Types of Nonprobability Sampling Purposive or judgmental sampling
• Selecting a sample based on knowledge of a population, its elements, and the purpose of the study.
• Used when field researchers are interested in studying cases that don’t fit into regular patterns of attitudes and behaviors
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Types of Nonprobability Sampling Snowball sampling
• Appropriate when members of a population are difficult to locate.
• Researcher collects data on members of the target population she can locate, then asks them to help locate other members of that population.
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Types of Nonprobability Sampling Quota sampling
• Begin with a matrix of the population.• Data is collected from people with the
characteristics of a given cell. • Each group is assigned a weight appropriate
to their portion of the population.• Data should provide a representation of the
total population.
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Probability Sampling Used when researchers want
precise, statistical descriptions of large populations.
A sample of individuals from a population must contain the same variations that exist in the population.
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Probability Sampling Most effective method for selection
of study elements. Avoids researchers biases in
element selection. Permits estimates of sampling
error.
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Populations and Sampling Frames Findings based on a sample represent
the aggregation of elements that compose the sampling frame.
Sampling frames do not always include all the elements their names imply.
All elements must have equal representation in the frame.
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Types of Sampling Designs Simple random sampling (SRS) Systematic sampling Stratified sampling
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Simple Random Sampling Feasible only with the simplest
sampling frame. Basic method assumed in most
statistical computations
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Systematic Sampling Slightly more accurate than simple
random sampling. Arrangement of elements in the
list can result in a biased sample.
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Stratified Sampling Rather than selecting sample for
population at large, researcher draws from homogenous subsets of the population.
Results in a greater degree of representativeness by decreasing the probable sampling error.
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Multistage Cluster Sampling Used when it's not possible or
practical to create a list of all the elements that compose the target population.
Involves repetition of two basic steps: listing and sampling.
Highly efficient but less accurate.