Describe why you were to choose a specific method to select a sample over other methods. Defend the method you preferred.
3 – 4 Paragraphs
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Chapter 15
Developing and Testing Self-Report Scales
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Question
Tell whether the following statement is true or false:
Scale development begins with a sound conceptualization of the construct (the latent variable) to be measured, excluding its dimensionality.
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Answer
False
Scale development begins with a sound conceptualization of the construct (the latent variable) to be measured, including its dimensionality.
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Conceptualizing the Construct
Scale development begins with a sound conceptualization of the construct (the latent trait) to be measured, including its dimensionality.
Unobservable latent trait
Unidimensional
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Type of Scale
Scale selection is done before items can be generated.
Two broad categories of multi-item reflective scales
Traditional summated rating (Likert)
Latent trait
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Generating Item Pool
Sources
Existing instruments
Research literature
Concept analyses
In-depth studies
Clinical observations
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Decisions about Item Features
Number of items
Response items
Positive and negative stems
Item intensity
Item time frames
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Number of Items
Domain sampling model: homogeneous set of items from a hypothetical universe of items
Goal is to provide appropriate redundancy so idiosyncrasies can be cancelled out.
Recommends starting with 3 to 4 times as many items as you will have in your final scale
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Response Options
Scale items contain:
A stem
Response options
For example, strongly disagree, disagree, agree, strongly agree
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Positive and Negative Stems
The objective was to include items that would minimize the possibility of an acquiescence response set—the tendency to agree with statements regardless of their content.
Many experts currently advise again including negative and positive items on a scale.
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Item Intensity
The intensity of the statements (stems) should be similar and fairly strongly worded.
Statements should not be so extremely worded as to result in universal rejection.
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Item Time Frames
A time frame should not emerge as a consequence of item development.
It should be decided upon in advance, based on the conceptual understanding of the construct and the needs for which the scale is being constructed.
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Wording the Items—Readability
Clarity
Jargon
Length
Double negatives
Double-barreled items
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Question
Once content validity has been established at a satisfactory level, the scale must be administered to a development sample. What is the typical number of respondents who are representative of the target population?
100
150
250
300
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Answer
D
Once content validity has been established at a satisfactory level, the scale must be administered to a development sample—typically 300 or more respondents who are representative of the target population.
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Content Validity
Satisfactory level
Development sample
300 or more respondents representative of target population
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Field Testing the Instrument
Developing the sampling plan
Developing a data collection plan
Preparing for data collection
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Question
Tell whether the following statement is true or false:
Exploratory factor analysis is used to reduce a small set of variables into a larger set of underlying dimensions, called factors.
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Answer
False
Exploratory factor analysis is used to reduce a large set of variables into a smaller set of underlying dimensions, called factors.
Copyright © 2017 Wolters Kluwer Health | Lippincott Williams & Wilkins
Analysis of Scale Development Data
Basic item analysis
Inter-item correlation
Item–scale correlations
Exploratory factor analysis (EFA)
Factor extraction
Principal components analysis (PCA)
Factor rotation—orthogonal or oblique
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Illustration of Factor Rotation
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Scale Refinement and Validation
Revising the scale
Scoring the scale
Conducting a validation study
Confirmatory factor analysis
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Confirmatory Factor Analysis
CFA is a second study often undertaken to validate the scale.
A subset of sophisticated statistical techniques (structural equation modeling)
Involves tests of a measurement model
Stipulates the hypothesized relationship between latent traits and manifest variables (items)
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Interpretability of Scale Scores
Interpretability: the degree to which one can assign qualitative meaning
Percentile
Standard scores
Norms
Cutoff points
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Critiquing Scale Development Studies
Methods used
Whether the evidence regarding the scale’s psychometric adequacy is sufficiently sound
See Box 15.1
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Chapter 16
Descriptive Statistics
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Question
Tell whether the following statement is true or false:
Nominal measurement is the ranking of objects based on their relative standing on an attribute.
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Answer
False
Nominal measurement: the classification of characteristics into mutually exclusive categories
Ordinal measurement: the ranking of objects based on their relative standing on an attribute
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Measurement
Nominal measurement: the classification of characteristics into mutually exclusive categories
Ordinal measurement: the ranking of objects based on their relative standing on an attribute
Interval measurement: indicating not only the ranking of objects but the amount of distance between them
Ratio measurement: distinguished from interval measurement by having a rational zero point
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Descriptive Statistics
Summarize quantitative data
Describe quantitative data
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Question
Tell whether the following statement is true or false:
Frequency distributions impose order on raw data. Numeric values are ordered from lowest to highest, accompanied by a count of the number of times each value was obtained.
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Answer
True
Frequency distributions impose order on raw data. Numeric values are ordered from lowest to highest, accompanied by a count of the number (or percentage) of times each value was obtained.
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Frequency Distributions
Impose order on raw data
Numeric values are ordered from lowest to highest, accompanied by a count of the number (or percentage) of times each value was obtained.
Common methods of display
Histograms
Frequency polygons
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Distribution
Symmetric: two halves are mirror images of each other
Skewed: asymmetric with one tail longer than the other
Positively skewed
Negatively skewed
Modality: number of peaks
Unimodal
Multimodal
Normal distribution
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Question
What is the median?
Average or typical value of a set of scores
Value that occurs most frequently in a distribution
Point above which and below which 50% of the cases fall
Arithmetic average of all scores
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Answer
C
Central tendency are indexes, expressed as a single number, that represent the average or typical value of a set of scores. The mode is the value that occurs most frequently in a distribution, the median is the point above which and below which 50% of the cases fall, and the mean is the arithmetic average of all scores.
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Central Tendency
Central tendency are indexes, expressed as a single number, that represent the average or typical value of a set of scores.
Mode: value that occurs most frequently in a distribution
Median: point above which and below which 50% of the cases fall
Mean: arithmetic average of all scores
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Question
Tell whether the following statement is true or false:
Range is the distance between the highest and lowest scores.
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Answer
True
Range is the distance between the highest and lowest scores.
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Variability
Variability: how spread out the data are
Range: distance between the highest and lowest scores
Standard deviation: indicates how much, on average, scores deviate from the mean
Calculation
Deviation scores represent the degree to which each person’s score deviates from the mean. The variance is equal to the SD squared.
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Bivariate Descriptive Statistics
Relationships between two variables
Contingency table two-dimensional frequency distribution in which the frequencies of two nominal- or ordinal-level variables are crosstabulated
Correlation coefficients describe the direction and magnitude of a relationship between two variables.
Product–moment correlation coefficient (Pearson’s r)—interval or ratio
Spearman’s rho coefficient—ordinal
Scatter plot
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Risk Indexes
Absolute risk reduction: expresses the estimated proportion of people who would be spared from an adverse outcome through exposure to an intervention
Relative risk: estimated proportion of the original risk of an adverse outcome that persists among people exposed to an intervention
Relative risk reduction: estimated proportion of untreated risk that is reduced through exposure to the intervention
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Risk Indexes
Odds ratio: ratio of the odds for the treated versus untreated group
Number needed to treat: estimate of how many people would need to receive the intervention to prevent one adverse outcome
