4.5: Reliability
- Page ID
- 124462
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)- Define reliability.
- List and describe the different types of reliability.
What is Reliability?
Reliability is the degree to which the measure of a construct is consistent or dependable. If a scale is used to measure the same construct multiple times, a reliable measure produces the same result each time, assuming the underlying phenomenon has not changed. For example, using a calibrated weight scale is a reliable measurement because it produces the same value repeatedly, whereas "guessing" a person's weight is unreliable due to inconsistent estimations.
It is critical to note that reliability implies consistency, not accuracy. If a scale is calibrated incorrectly, for instance, consistently shaving off ten pounds, it remains a reliable measure because it provides consistent results, even though those results are not valid (accurate).
Sources of unreliability in social science often stem from:
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Researcher Subjectivity: When measurement depends on observer interpretation (e.g., inferring morale from observation), results may vary by observer or by the timing of the observation.
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Ambiguity: Imprecise questions (e.g., asking for "salary" without specifying annual or monthly) lead to divergent responses.
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Lack of Respondent Familiarity: Asking respondents about issues they do not understand or care about results in unreliable data.
Reliability can be improved by using quantitative rather than qualitative measures, simplifying survey wording, and ensuring questions are clear and relevant. However, because these strategies do not guarantee perfect results, measurement instruments must be empirically tested for reliability.
Some Types of Reliability
1. Inter-Rater Reliability
This measures consistency between two or more independent people observing the same thing. For example, if two researchers are watching a classroom to count the number of times a student raises their hand, they should produce very similar counts. If their counts match most of the time, the observation process is reliable.
2. Test-Retest Reliability
This measures consistency by testing the same people twice. The same survey or test is given to the same group at two different times. If the results are similar both times, the measure is reliable. The time interval between the two tests is important; if too much time passes, the participants might actually change, which makes it harder to measure consistency.
3. Split-Half Reliability
This measures consistency by looking at different parts of the same test. If you have a long survey with many questions about one topic, you can randomly split the questions into two equal groups. If a respondent’s score on the first half of the questions matches their score on the second half, the instrument is likely reliable.
4. Internal Consistency Reliability
This assesses whether all the different items in a single survey are measuring the same thing. If a survey has multiple questions about "job satisfaction," you would expect a person who answers "highly satisfied" to one question to answer positively to the other questions as well. If the items are consistent with each other, the survey has high internal consistency.
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Reliability: The degree to which a measure is consistent or dependable over multiple applications.
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Inter-Rater Reliability: Consistency between two or more independent observers.
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Test-Retest Reliability: Stability of a measure when the same group is tested twice over time.
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Split-Half Reliability: Consistency by comparing results from two halves of the same test.
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Internal Consistency: Whether all items in a single survey measure the same underlying construct.