Reliability, Validity, and Multiple-Item Scales in Statistics MCQs
Reliability, Validity, and Multiple-Item Scales in Statistics MCQs
Welcome to MCQss.com, your source for MCQs on reliability, validity, and multiple-item scales in statistics. This page offers a collection of interactive MCQs designed to assess your understanding of these important concepts and their application in research.
Reliability refers to the consistency and stability of measurement. It examines the extent to which a measurement instrument produces consistent results over time, across different conditions, or when administered by different raters. Our MCQs cover topics related to different types of reliability, such as test-retest reliability, inter-rater reliability, and internal consistency reliability. You can test your knowledge of the factors that affect reliability estimates and the methods used to assess reliability.
Validity, on the other hand, refers to the extent to which a measurement instrument accurately measures the construct or concept it intends to measure. Our MCQs explore various types of validity, including content validity, criterion-related validity, and construct validity. You can assess your understanding of validation methods such as face validity, concurrent validity, and convergent/divergent validity.
Multiple-item scales are commonly used in research to measure complex constructs. Our MCQs cover topics related to the development and assessment of multiple-item scales, including item analysis techniques, scale reliability estimation (e.g., Cronbach's alpha), and exploratory and confirmatory factor analysis for scale validation.
Engaging with these MCQs will not only test your knowledge but also enhance your understanding of the concepts and methods associated with reliability, validity, and multiple-item scales in statistics. Whether you are a student, researcher, or practitioner, these MCQs will help you sharpen your skills in designing, evaluating, and using measurement instruments effectively.
Explore the MCQs now and challenge yourself to expand your expertise in reliability, validity, and multiple-item scales.
1: A statistic that assesses the degree of agreement in the assignment of categories made by two judges or observers (correcting for chance levels of agreement) is known as:
A. Internal Consistency Reliability
B. Cohen’s Kappa [κ]
C. Cronbach’s alpha (α)
D. None of these
2: An index of internal consistency reliability that assesses the degree to which responses are consistent across a set of multiple measures of the same construct, usually self-report items is known as:
A. Internal Consistency Reliability
B. Cohen’s Kappa [κ]
C. Cronbach’s alpha (α)
D. None of these
3: Consistency or agreement across a number of measures of the same construct, usually multiple items on a self-report test is known as:
A. Internal Consistency Reliability
B. Cohen’s Kappa [κ]
C. Cronbach’s alpha (α)
D. None of these
4: When a correlation is obtained to index split-half reliability, that correlation actually indicates the reliability or consistency of a scale with p/2 items is called __________ .
A. Split-Half Reliability
B. Spearman-Brown Prophecy Formula
C. Parallel-Forms Reliability
D. Kuder-Richardson 20 (KR-20)
5: Kuder-Richardson 20 (KR-20) is the name given to Cronbach’s alpha when all items are dichotomous. See also internal consistency reliability.
A. Split-Half Reliability
B. Spearman-Brown Prophecy Formula
C. Parallel-Forms Reliability
D. Kuder-Richardson 20 (KR-20)
6: A type of internal consistency reliability assessment that is used with multiple-item scales. The set of p items in the scale is divided (either randomly or systematically) into two sets of p/2 items is known as:
A. Split-Half Reliability
B. Spearman-Brown Prophecy Formula
C. Parallel-Forms Reliability
D. Kuder-Richardson 20 (KR-20)
7: When a test developer creates two versions of a test (which contain different questions but are constructed to include items that are matched in content) is called ___________ .
A. Split-Half Reliability
B. Spearman-Brown Prophecy Formula
C. Parallel-Forms Reliability
D. Kuder-Richardson 20 (KR-20)
8: The degree to which an X variable really measures the construct that it is supposed to measure is known as:
A. Projective Tests
B. Face Validity
C. Content Validity
D. Construct Validity
9: The degree to which the content of questions in a self-report measure covers the entire domain of material that should be included (based on theory or assessments by experts) is known as:
A. Projective Tests
B. Face Validity
C. Content Validity
D. Construct Validity
10: The degree to which it is obvious what attitudes or abilities a test measures from the content of the questions posed is called __________ .
A. Projective Tests
B. Face Validity
C. Content Validity
D. Construct Validity
11: Tests that involve the presentation of ambiguous stimuli (such as Rorschach inkblots or thematic apperception test drawings) is known as:
A. Projective Tests
B. Face Validity
C. Content Validity
D. Construct Validity
12: _____________ _ is the degree to which a new measure, X', correlates with an existing measure, X, that is supposed to measure the same construct .
A. Empirical Keying
B. Convergent Validity
C. Discriminant Validity
D. None of these
13: Discriminant Validity means our theories tell us that a measure X should be unrelated to other variables such as Y, a correlation of near 0 is taken as evidence of discriminant validity, that is, evidence that X does not measure things it should not be measuring.
A. True
B. False
14: A method of scale construction in which items are selected for inclusion in the scale because they have high correlations with the criterion of interest is known as:
A. Empirical Keying
B. Convergent Validity
C. Discriminant Validity
D. None of these
Reliability, Validity, and Multiple-Item Scales in Statistics MCQs
