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Factor Analysis
Not all research is focused on hypothesis testing. Sometimes researchers are interested in identifying the structure of a particular phenomenon. For example, suppose a team of researchers were interested in developing a tool that would adequately measure and reflect the concerns of women considering undergoing genetic testing for familial breast cancer. A literature review indicated to these researchers that the structure of this construct called concern had been identified and described for other populations (e.g., adult caregivers of cancer patients) but needed to be redefined for their population of interest: women at risk for familial breast cancer. The methods of factor analysis can be used in developing such an instrument.
Characteristics of Factor Analysis
Factor analysis is not a single statistical method. Rather, it involves a complex ...
- Behavioral and Social Science
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- Radiation
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- Social Capital and Health
- Social Hierarchy and Health
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- History and Biography
- Budd, William
- Doll, Richard
- Ehrlich, Paul
- Epidemiology, History of
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- Frost, Wade Hampton
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- Etiology of Disease
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- Gestational Age
- Intent-to-Treat Analysis
- International Classification of Diseases
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- Latency and Incubation Periods
- Life Course Approach
- Malnutrition, Measurement of
- Medical Anthropology
- Organ Donation
- Pain
- Placebo Effect
- Preclinical Phase of Disease
- Preterm Birth
- Public Health Nursing
- Quarantine and Isolation
- Screening
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- Specific Populations
- African American Health Issues
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- Breastfeeding
- Child and Adolescent Health
- Epidemiology in Developing Countries
- Hormone Replacement Therapy
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- Maternal and Child Health Epidemiology
- Men's Health Issues
- Oral Contraceptives
- Race and Ethnicity, Measurement Issues With
- Race Bridging
- Rural Health Issues
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- Urban Health Issues
- Women's Health Issues
- Statistics and Research Methods
- F Test
- p Value
- Additive and Multiplicative Models
- Analysis of Covariance
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- Bar Chart
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- Collinearity
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- Cox Model
- Critical Value
- Cumulative Incidence
- Data Management
- Data Transformations
- Decision Analysis
- Degrees of Freedom
- Dependent and Independent Variables
- Diffusion of Innovations
- Discriminant Analysis
- Dose-Response Relationship
- Doubling Time
- Dummy Coding
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- Ecological Fallacy
- Economic Evaluation
- Effect Modification and Interaction
- Factor Analysis
- Fisher's Exact Test
- Geographical and Spatial Analysis
- Graphical Presentation of Data
- Halo Effect
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- Hazard Rate
- Healthy Worker Effect
- Hill's Considerations for Causal Inference
- Histogram
- Hypothesis Testing
- Inferential and Descriptive Statistics
- Intent-to-Treat Analysis
- Internet Data Collection
- Interquartile Range
- Interrater Reliability
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- Null and Alternative Hypotheses
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- Program Evaluation
- Propensity Score
- Proportion
- Qualitative Methods in Epidemiology
- Quasi Experiments
- Questionnaire Design
- Race Bridging
- Random Variable
- Random-Digit Dialing
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- Rate
- Ratio
- Receiver Operating Characteristic (ROC) Curve
- Regression
- Relational Database
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- Response Rate
- Robust Statistics
- Sample Size Calculations and Statistical Power
- Sampling Distribution
- Sampling Techniques
- Scatterplot
- Secondary Data
- Sensitivity and Specificity
- Sequential Analysis
- Simpson's Paradox
- Skewness
- Spreadsheet
- Stem-and-Leaf Plot
- Stratified Methods
- Structural Equation Modeling
- Study Design
- Survival Analysis
- Target Population
- Time Series
- Type I and Type II Errors
- Unit of Analysis
- Validity
- Volunteer Effect
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