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Literature Review
Literature reviews are systematic syntheses of previous work around a particular topic. Nearly all scholars have written literature reviews at some point; such reviews are common requirements for class projects or as part of theses, are often the first section of empirical papers, and are sometimes written to summarize a field of study. Given the increasing amount of literature in many fields, reviews are critical in synthesizing scientific knowledge. Although common and important to science, literature reviews are rarely considered to be held to the same scientific rigor as other aspects of the research process. This entry describes the types of literature reviews and scientific standards for conducting literature reviews.
Types of Literature Reviews
Although beginning scholars often believe that there is one predefined approach, various types of literature reviews exist. Literature reviews can vary along at least seven dimensions.
Focus
The focus is the basic unit of information that the reviewer extracts from the literature. Reviews most commonly focus on research outcomes, drawing conclusions of the form of “The research shows X” or “These studies find X whereas other studies find Y.” Although research outcomes are most common, other foci are possible. Some reviews focus on research methods, for example, considering how many studies in a field use longitudinal designs. Literature reviews can also focus on theories, such as what theoretical explanations are commonly used within a field or attempts to integrate multiple theoretical perspectives. Finally, literature reviews can focus on typical practices within a field, for instance, on what sort of interventions are used in clinical literature or on the type of data analyses conducted within an area of empirical research.
Goals
Common goals include integrating literature by drawing generalizations (e.g., concluding the strength of an effect from several studies), resolving conflicts (e.g., why an effect is found in some studies but not others), or drawing links across separate fields (e.g., demonstrating that two lines of research are investigating a common phenomenon). Another goal of a literature review might be to identify central issues, such as unresolved questions or next steps for future research. Finally, some reviews have the goal of criticism; although this goal might sound unsavory, it is important for scientific fields to be evaluated critically and have shortcomings noted.
Perspective
Literature reviews also vary in terms of perspective, with some attempting to represent the literature neutrally and others arguing for a position. Although few reviews fall entirely on one end of this dimension or the other, it is useful for readers to consider this perspective when evaluating a review and for writers to consider their own perspective.
Coverage
Coverage refers to the amount of literature on which the review is based. At one extreme of this dimension is exhaustive coverage, which uses all available literature. A similar approach is the exhaustive review with selective citation, in which the reviewer uses all available literature to draw conclusions but cites only a sample of this literature when writing the review. Moving along this dimension, a review can be representative, such that the reviewer bases conclusions on and cites a subset of the existing literature believed to be similar to the larger body of work. Finally, at the far end of this continuum is the literature review of most central works.
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- Descriptive Statistics
- Distributions
- Graphical Displays of Data
- Hypothesis Testing
- Alternative Hypotheses
- Beta
- Critical Value
- Decision Rule
- Hypothesis
- Nondirectional Hypotheses
- Nonsignificance
- Null Hypothesis
- One-Tailed Test
- p Value
- Power
- Power Analysis
- Significance Level, Concept of
- Significance Level, Interpretation and Construction
- Significance, Statistical
- Two-Tailed Test
- Type I Error
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- Important Publications
- “Coefficient Alpha and the Internal Structure of Tests”
- “Convergent and Discriminant Validation by the Multitrait-Multimethod Matrix”
- “Meta-Analysis of Psychotherapy Outcome Studies”
- “On the Theory of Scales of Measurement”
- “Probable Error of a Mean, The”
- “Psychometric Experiments”
- “Sequential Tests of Statistical Hypotheses”
- “Technique for the Measurement of Attitudes, A”
- “Validity”
- Aptitudes and Instructional Methods
- Doctrine of Chances, The
- Logic of Scientific Discovery, The
- Nonparametric Statistics for the Behavioral Sciences
- Probabilistic Models for Some Intelligence and Attainment Tests
- Statistical Power Analysis for the Behavioral Sciences
- Teoria Statistica Delle Classi e Calcolo Delle Probabilità
- Inferential Statistics
- Association, Measures of
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- Split-Plot Factorial Design
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- Within-Subjects Design
- Zelen's Randomized Consent Design
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- Clinical Significance
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- External Validity
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- Multiple Treatment Interference
- Multivalued Treatment Effects
- Nonclassical Experimenter Effects
- Order Effects
- Placebo Effect
- Pretest Sensitization
- Random Assignment
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- Selection
- Sequence Effects
- Threats to Validity
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- Volunteer Bias
- White Noise
- Sampling
- Cluster Sampling
- Convenience Sampling
- Demographics
- Error
- Exclusion Criteria
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- Sampling
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- Scaling
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- Cohen's Kappa
- Collinearity
- Correlation
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- Disturbance Terms
- Error Rates
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- Residuals
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- Sums of Squares
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- Accuracy in Parameter Estimation
- Analysis of Covariance (ANCOVA)
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- Barycentric Discriminant Analysis
- Bivariate Regression
- Bonferroni Procedure
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- Confirmatory Factor Analysis
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- Dummy Coding
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- Greenhouse-Geisser Correction
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- Jackknife
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- Logistic Regression
- Mean Comparisons
- Missing Data, Imputation of
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- Stepwise Regression
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- Yates's Correction
- Statistical Tests
- Bartlett's Test
- Behrens-Fisher t′ Statistic
- Chi-Square Test
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- Fisher's Least Significant Difference Test
- Friedman Test
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- Kolmogorov-Smirnov Test
- Kruskal-Wallis Test
- Mann-Whitney U Test
- Mauchly Test
- McNemar's Test
- Multiple Comparison Tests
- Newman-Keuls Test and Tukey Test
- Omnibus Tests
- Scheffé Test
- Sign Test
- t Test, Independent Samples
- t Test, One Sample
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- Tukey's Honestly Significant Difference (HSD)
- Welch's t Test
- Wilcoxon Rank Sum Test
- z Test
- Theories, Laws, and Principles
- Bayes's Theorem
- Central Limit Theorem
- Classical Test Theory
- Correspondence Principle
- Critical Theory
- Falsifiability
- Game Theory
- Gauss-Markov Theorem
- Generalizability Theory
- Grounded Theory
- Item Response Theory
- Occam's Razor
- Paradigm
- Positivism
- Probability, Laws of
- Theory
- Theory of Attitude Measurement
- Weber-Fechner Law
- Types of Variables
- Validity of Scores
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