Correlational Research and Survey Reliability

Correlational Research

Correlational Research

Research method assessing relationships between variables.

Surveys

Commonly used tools for correlational research.

Reliability

Consistency of a measure across time or items.

Validity

Accuracy of a measure in assessing intended variables.

Internal Consistency Reliability

Degree items in a scale are interrelated.

Cronbach's Alpha

Statistic measuring internal consistency reliability.

Test-Retest Reliability

Stability of a measure over time.

Alternative-Form Reliability

Correlation between two different versions of a measure.

Inter-Rater Reliability

Agreement between different raters observing the same behavior.

Percent Agreement

Common metric for inter-rater reliability assessment.

Kappa Coefficient

Statistical measure of inter-rater agreement.

Face Validity

Surface-level assessment of whether a scale measures intended variable.

Content Validity

Extent items reflect the range of material for measurement.

Construct Validity

Degree a scale measures the desired construct.

Convergent Validity

Measure correlates with expected related measures.

Discriminant Validity

Measure does not correlate with unrelated measures.

Criterion Validity

Relation of measurement to a specific outcome.

Concurrent Validity

Measure corresponds to existing outcomes or behaviors.

Predictive Validity

Measure predicts future outcomes or behaviors.

Correlation Coefficient

Indicates strength and direction of variable association.

Pearson r

Ranges from -1.0 to +1.0 indicating correlation strength.

Third Variable Problem

Unaccounted variable affecting correlation between two variables.

Temporal Precedence

Establishing cause-effect relationship by timing.

Scatter Plot

Graphical representation of relationship between two variables.

Continuous Variables

Variables that can take any value within a range.

Categorical Variables

Variables that represent distinct categories or groups.

Point-Biserial Correlation

Correlation between continuous and dichotomous variables.

Dichotomous Variable

Variable with two distinct categories or levels.

Dummy Coding

Assigns numerical values to dichotomous variables.

Phi Coefficient

Measures correlation between two dichotomous variables.

ANOVA

Analyzes differences among group means.

ANCOVA

Combines ANOVA with regression to control covariates.

Multiple Regression Analysis

Predicts outcome based on multiple predictor variables.

Logistic Regression Analysis

Predicts binary outcomes from predictor variables.

Factor Analysis

Identifies underlying relationships between variables.

Cluster Analysis

Groups similar objects based on characteristics.

Structural Equation Modeling (SEM)

Tests complex relationships among variables.

MANOVA

Multivariate analysis of variance for multiple dependent variables.

MANCOVA

MANOVA with covariate control.

Census-Style Counts

Counts all individuals in a population.

Service Utilization

Measures use of services like shelters.

Household Surveys

Collects data from households about homelessness.

Lifetime Prevalence

Total number of individuals experiencing homelessness.

Point Prevalence

Homelessness status at a specific time.

Sympathy Index

Measures public sympathy towards homeless individuals.

Age Differences

Variations in experiences across different age groups.

Univariate F

Statistical test for comparing means of groups.

Post-hoc Analysis

Tests conducted after ANOVA to find specific group differences.

Brief Symptom Inventory

Assesses psychological distress symptoms.

Homeless Experience

Refers to duration and conditions of homelessness.

Social Support

Resources provided by family and friends.

Physical Symptoms

Physical health issues related to stress or homelessness.