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Discussion Question

1- Discussion question: Describe why you were to chose a specific method to select a sample over other methods. Defend the method you preferred.

2- APA Style

3- 3 paragraph 3 sentences each

4- 2 references not older than 2015

Chapter

3
Sampling in Quantitative Research

Question #1

Tell whether the following statement is true or false:

The aggregate of cases in which a researcher is interested is called a sample.

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Answer to Question #1
False
The aggregate of cases in which a researcher is interested is called a population. A sample is selection of a portion of the population to represent the entire population.

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Basic Sampling Concepts in Quantitative Studies #1
Population: the aggregate of cases in which a researcher is interested
Accessible population: the aggregate of cases that conform to designated criteria and that are accessible for a study
Target population: the aggregate of cases about which the researcher would like to generalize

Basic Sampling Concepts in Quantitative Studies #2
Eligibility criteria/inclusive criteria: criteria that specify population characteristics
Cost
Practical constraints
People’s ability to participate
Design considerations
Exclusion criteria

Basic Sampling Concepts in Quantitative Studies #3
Samples and Sampling
Sampling: selection of a portion of the population (a sample) to represent the entire population
Element: basic population unit about which information is collected
Sample: a subset of population elements
Representative sample
Probability sample
Nonprobability sample

Question #2
Tell whether the following statement is true or false:
Researchers usually sample from the target population.

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Answer to Question #2
False
Researchers usually sample from the accessible population but should identify the target population to which they want to generalize their results.

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Basic Sampling Concepts in Quantitative Studies #4
Staged sample: samples are sometimes selected in multiple phases
Sampling bias: the systematic over- or underrepresentation of segments of the population on key variables

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Question #3
Tell whether the following statement is true or false:
Probability sampling involves random selection of elements.

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Answer to Question #3
True
Probability sampling involves random selection of elements.

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Nonprobability Sampling
Convenience sampling
Snowball sampling
Quota sampling
Consecutive sampling
Purposive sampling
Evaluation of nonprobability sampling

Probability Sampling
Simple random sampling
Stratified random sampling
Multistage sampling
Cluster sampling
Systematic sampling
Evaluation of probability sampling

Sample Size in Quantitative Studies
Power analysis
Estimate sample size
Large samples preferred to small samples
Sample size basics
Factors affecting sample size /requirements in quantitative research
Effect size
Homogeneity of the population
Cooperation and attrition
Subgroup analyses

Implementing a Quantitative Sampling Plan
Steps in sampling
Identify the population
Specify the eligibility criteria
Specify the sampling plan
Recruit the sample
Sample recruitment
Screening instrument
Generalizing from samples

Critical Appraisal of Sampling Plans #1
Sampling Plan
Construct
Internal factors
External factors
Statistical conclusion validity

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Critical Appraisal of Sampling Plans #2
Sampling plan should be scrutinized with respect to
Approach used
Study population and eligibility criteria
Number of participants and rationale for sample size
Inclusion of power analysis
Description of main characteristics of sample
Number and characteristics of participants who declined participation/dropped out

Chapter

4
Data Collection in Quantitative Research

Question #1

Tell whether the following statement is true or false:

For unstructured data, researchers use formal data collection instruments that place constraints on those collecting data and those providing them.

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Answer to Question #1
False
For structured data, not unstructured data, researchers use formal data collection instruments that place constraints on those collecting data and those providing them.

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Developing a Data Collection Plan
Identifying data needs
Selecting types of measures
Selecting and developing instruments
Pretesting the data collection package
Developing data collection forms and procedures

Early Steps in Data Collection Plan
Identification and prioritization of data needs
Measures of variables
Selection of existing instruments
Conceptual stability
Data quality
Cost
Population appropriateness
Reputation

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Question #2
Tell whether the following statement is true or false:
Open-ended questions permit respondents to reply in narrative fashion.

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Answer to Question #2
True
Open-ended questions permit respondents to reply in narrative fashion, whereas closed-ended (or fixed-alternative) questions offer response alternatives from which respondents must choose.

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Structured Self-Report Instruments
Interview schedules
Questionnaires
Open-ended questions
Closed-ended questions

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Open- and Closed-Ended Questions
Open-ended questions allow people to respond in their own words, in narrative fashion
Questionnaires/interviews
Closed-ended answers may range from a simple yes or no to complex expressions of opinion or behavior
Dichotomous
Multiple choice
Rank order
Forced choice
Rating
Checklists
Visual analog scales

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Question #3
Which type of closed-ended questions have several questions with the same response format?
Forced choice
Rating
Checklist
Visual analog scale

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Answer to Question #3
C
Forced-choice questions require respondents to choose between two competing positions; rating questions ask respondents to make judgments along a bipolar dimension; checklists have several questions with the same response format; and visual analog scales (VASs) are continually used to measure subjective experiences.

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Composite Scales and Other Structured Self-Reports
Likert scale
Summated rating scale
Series of statements about a phenomenon
Indicate degree of agreement or disagreement
Total score is computed by summing item scores, each of which is scored for the intensity and direction of favorability
Cognitive and neuropsychological tests
Intelligence
Aptitude

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Other Types of Structured Self-Reports: Semantic Differentials
Bipolar rating scales
Indicate reactions toward a phenomenon
Measure
Evaluative
Activity
Potency

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Other Types of Structured Self-Reports:
Q Sort
Sort a set of card statements into piles
Specified criteria
Measure
Attitude
Personality
Psychological traits

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Other Types of Structured Self-Reports: Vignettes
Brief descriptions of the event
Asked to react to events
Assess respondents’
Perceptions
Hypothetical behaviors
Decisions

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Question #4
Tell whether the following statement is true or false:
Interviews are less costly and time-consuming than questionnaires.

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Answer to Question #4
False
Questionnaires are less costly and time-consuming than interviews.

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Questionnaires Vs. Interviews #1
Questionnaires
Less costly
Possibility of anonymity
No risk of interviewer bias

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Questionnaires Vs. Interviews #2
Interviews
Higher response rate
Wider variety of people
Clarity
Depth of questioning
Less missing information
More supplementary data

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Designing Structured Self-Reports
Response set biases
Common responses
Social desirability
Extreme response
Acquiescence

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Methods of Recording Structured Observations: Checklists
Occurrence or frequency
Category systems

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Methods of Recording Structured Observations: Rating Scales
Rate phenomena
Dimension typically bipolar
Made at specific intervals or after observations are complete

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Sampling for Structured Observation: Sampling
Time sampling involves the specification of the duration and frequency of observational periods and intersession intervals.
Event sampling selects integral behaviors or events of a special type for observation.

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Evaluation of Structured Observation: Biases
Halo effect
Assimilatory biases
Errors of leniency
Errors of severity

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Biomarkers
Selecting
In vivo
In vitro
Considerations
Necessary equipment available?
Difficult to secure permission?
Will a single measure of outcome be sufficient?
Will measures be influenced by reactivity?
Are safety precautions familiar?

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Biomarkers: Evaluation
Advantages
Accurate/precise/objective
Valid measures of variables
Disadvantages
Cost
Measuring tools affect variables
Biomarkers may be damaged
Varying lab protocols
Biased norm values

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Physical Performance Tests
Patients’ abilities and skills are sometimes measured with performance tests.
6-mile walk test

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Data Extracted From Records
Needed
Trained abstractors
Abstractors blinded to the study
Explicated records inclusion and exclusion criteria
Defined variables of interest
Unambiguous guidelines
Clear-cut rules
Frequent accuracy checks
Verification by random sampling

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Implementing a Data Collection Plan
Considerations to keep in mind when selecting research personnel
Experience
Congruency
Appearance
Personality
Training

Chapter

5
Measurement and Data Quality

Question #1

Tell whether the following statement is true or false:

Measurement involves assigning numbers to objects to represent the amount of an attribute.

Copyright © 2021 Wolters Kluwer Health | Lippincott Williams & Wilkins
Answer to Question #1
True
Measurement involves assigning numbers to objects to represent the amount of an attribute, using a specified set of rules. Researchers strive to develop or use measurements whose rules are isomorphic with reality.

Copyright © 2021 Wolters Kluwer Health | Lippincott Williams & Wilkins
Measurement
The assignment of numbers to represent the amount of an attribute present in an object or person, using specific rules
Rules are necessary to promote consistency and interpretability
Advantages
Removes guesswork
Provides precise information
Less vague than words

Theories of Measurement
Psychometrics is a branch of psychology concerned with the theory and methods of psychological measurement.
Two theories
Classical test theory (CTT)
Item response theory (IRT)

Errors of Measurement
Obtained score = True score + Error
Obtained score: an actual data value for a participant
True score: value that would be obtained for a hypothetical perfect measure attribute
Error of measurement: represents measurement inaccuracies

Factors That Contribute to Errors of Measurement
Situational contaminants
Transitory personal factors
Response-set biases
Administration variations
Instrument clarity
Item sampling

Major Types of Measures
Generic
Specific
Static
Adaptive
Reflective scales
Formative indexes

Measurement Taxonomy
Four measurement property domains
Cross-sectional domains
Reliability
Validity
Longitudinal measurement domains
Reliability of change scores
Responsiveness

Measurement and Statistics
Correlation coefficients
Correlation coefficients indicate direction and magnitude of relationships between variables.
Pearson’s r
Range:
From −1.00 (perfect negative correlation)
Through 0.00 (no correlation)
To +1.00 (perfect positive correlation)

Reliability #1
Consistency—the absence of variation in measuring a stable attribute for an individual
Reliability assessments involve computing a reliability coefficient
Most reliability coefficients are based on correlation coefficients.

Question #2
Tell whether the following statement is true or false:
Reliability coefficients usually range from .00 to 1.00, with higher values reflecting less reliability.

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Answer to Question #2
False
Reliability coefficients usually range from .00 to 1.00, with higher values reflecting greater reliability, not less reliability.

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Reliability #2
Replication approaches
Test–retest reliability: administration of the same measure to the same people on two occasions
Interrater reliability: measurements by two or more observers or raters using the same instrument or measurements by the same observer or rater on two or more occasions
Parallel test reliability: measurements of the same attribute using alternate versions of the same instrument, with the same people

Reliability Coefficient (R)
Represent the proportion of true variability to obtained variability:
R = VT
Vo
Should be at least .70; .80 preferable
Can be improved by making instrument longer (adding items)
Are lower in homogeneous than in heterogeneous samples

Internal Consistency
The extent to which all the instrument’s items are measuring the same attribute
Evaluated by administering the instrument on one occasion
Appropriate for most multi-item instruments
Most widely used evaluation method is the coefficient alpha

Measurement Error
Unless a reliability coefficient is 1.0 (virtually never happens), measurement error is present.
Used to estimate the range within which the true score lies
Standard error of measurement (SEM)
Limits of agreement (LOA)
Measurement error is routinely estimated for multi-item measures developed with item response theory (IRT) methods.

Validity
The degree to which an instrument measures what it is supposed to measure (resilience)
Four aspects of validity
Face validity
Content validity
Criterion-related validity
Construct validity

Face Validity
Refers to whether the instrument looks as though it is measuring the appropriate construct
Based on judgment, no objective criteria for assessment

Content Validity
The degree to which an instrument has an appropriate sample of items for the construct being measured
Relevance
Comprehensiveness
Balance
Evaluated by expert evaluation, via the content validity index (CVI)

Criterion Validity #1
The degree to which the instrument correlates with an external criterion or “gold standard”
Focal measures
Expense, efficiency, risk and discomfort, criterion unavailable, and prediction

Criterion Validity #2
Two types of criterion-related validity
Predictive validity: the instrument’s ability to distinguish people whose performance differs on a future criterion
Concurrent validity: the instrument’s ability to distinguish individuals who differ on a present criterion
Specificity, sensitivity
Predictive values
Likelihood ratios
Receiver operating characteristic curve (ROC curve), area under the curve (AUC)

Construct Validity
Concerned with the questions
What is this instrument really measuring?
Does it adequately measure the construct of interest?

Methods of Assessing Construct Validity
Hypothesis-testing validity
Convergent validity
Known-groups validity
Divergent validity (discriminant validity)
Multitrait–multimethod matrix method (MTMM)
Structural validity
Cross-cultural validity

Reliability of Change Scores
Change score: represents the amount of change between two scores
Difference score: the difference between the randomized groups at posttest
Smallest detectable change (SDC): a change in scores that is beyond measurement error
Reliable change index (RCI): assesses the clinical significance of improvement during a psychotherapeutic intervention

Responsiveness
The ability of a measure to detect change over time in a construct that has changed, commensurate with the amount of change that has occurred
Whether a change score is truly capturing a real change in the construct

Question #3
Tell whether the following statement is true or false:
Reliability is the degree to which an instrument measures what it is supposed to measure.

Copyright © 2021 Wolters Kluwer Health | Lippincott Williams & Wilkins
Answer to Question #3
False
Validity is the degree to which an instrument measures what it is supposed to measure. Reliability is the degree of consistency or accuracy with which an instrument measures an attribute.

Copyright © 2021 Wolters Kluwer Health | Lippincott Williams & Wilkins
Critiquing Data Quality in Quantitative Studies
Can I trust the data in this study?
Are the measurements of key constructs reliable and valid, and are change scores reliable and responsive?

Psychometric Assessment
Gather evidence
Validity
Reliability
Other assessment criteria

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