WayOf Psychology

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|•• RESEARCH METHODOLOGY••|

Mixed-Effects Models

    - Combines fixed effects (population-level effects) and random effects (individual-level variability).     - Useful in longitudinal and hierarchical data.

Latent Variable Models

    - Includes variables not directly observed but inferred from other variables.     - Examples include latent class analysis and latent growth modeling.

Path Analysis

    - Extension of regression analysis.     - Models direct and indirect relationships between variables.

Quasi-Experimental Design

    - Resembles experimental design but lacks random assignment.     - Includes designs like nonequivalent control group and interrupted time series.

Meta-Synthesis

    - Integrates findings from multiple qualitative studies.     - Provides a comprehensive understanding of a research topic.

Confirmatory Factor Analysis (CFA)

    - Tests hypotheses about the structure of latent variables.     - Confirms if data fits a predefined factor structure.

Item Response Theory (IRT)

    - Models the relationship between latent traits and item responses.     - Used in test construction and psychometrics.

Ecological Validity

    - Extent to which research findings generalize to real-world settings.     - Important for applied research.

Mediation and Moderation

    - Mediation°° Explains the process through which an independent variable influences a dependent variable.     - Moderation°° Examines how the relationship between two variables changes across levels of a third variable.

Longitudinal Data Analysis

    - Analyzes data collected over time from the same subjects.     - Techniques include growth curve modeling and repeated measures ANOVA.

Ethnographic Research

    - In-depth study of people and cultures.     - Involves participant observation and fieldwork.

Grounded Theory

    - Develop theory grounded in data.     - Iterative process of data collection and analysis.

Phenomenological Research

    - Explores lived experiences of individuals.     - Focuses on subjective meanings and interpretations.

Narrative Analysis

    - Examines stories and personal accounts.     - Identifies themes, structures, and meanings.

Experimental Manipulation Checks

    - Assesses if the manipulation in an experiment was successful.     - Ensures validity of experimental findings.

Latent Class Analysis (LCA)

    - Identifies subgroups within a population based on response patterns.     - Used in behavioral and social sciences.

Counterbalancing

    - Controls for order effects in repeated measures designs.     - Ensures each condition appears equally across all participants.

Content Validity

    - Ensures a measure covers all aspects of the construct.     - Assessed by expert judgment.

Ecological Momentary Assessment (EMA)

    - Collects data in real-time from participants' natural environments.     - Reduces recall bias and enhances ecological validity.

Behavioral Coding

    - Systematically records and categorizes observed behaviors.     - Used in observational studies and experimental research.

|••STATISTICS ••|

Multivariate Analysis

- Analysis involving multiple dependent and independent variables. - Techniques include MANOVA, multiple regression, and factor analysis.

Structural Equation Modeling (SEM)

- Statistical technique for testing and estimating causal relationships. - Combines factor analysis and multiple regression.

Logistic Regression

- Predicts the probability of a binary outcome. - Used when the dependent variable is categorical.

Hierarchical Linear Modeling (HLM)

- Analyzes data with nested structures (e.g., students within schools). - Accounts for variability at multiple levels.

Survival Analysis

- Analyzes time-to-event data. - Commonly used in clinical trials and reliability engineering.

Cluster Analysis

- Groups similar data points into clusters. - Methods include k-means and hierarchical clustering.

Discriminant Analysis

- Classifies data into predefined categories. - Determines which variables discriminate between categories.

Principal Component Analysis (PCA)

- Reduces data dimensionality by transforming variables into principal components. - Highlights the most important variables.

Bayesian Statistics

- Incorporates prior knowledge or beliefs in the analysis. - Updates probabilities as new data becomes available.

Non-Parametric Tests

- Do not assume a specific data distribution. - Examples include the Mann-Whitney U test, Wilcoxon signed-rank test, and Kruskal-Wallis test.

|••ON THIS DAY-June 8••|

1948

- B. F. Skinner's *Walden Two* was published. - Publisher Macmillan agreed only if Skinner wrote an introductory text.

1953

- The American Psychological Foundation (APF) was incorporated. - APF was created to support psychology projects financially. - J. McVicker Hunt was the first president.

1956

- Joseph V. Brady's article "Assessment of Drug Effects on Emotional Behavior" was published in *Science*. - Reported effects of reserpine on anxiety responses. - Led to behavioral pharmacology labs in major U.S. pharmaceutical companies.

1960

- The Psychology Society was founded in New York. - Promotes the interests of psychological practitioners.

1965

- APA Executive Director Arthur Brayfield testified before a U.S. Senate subcommittee. - Discussed the constitutionality of non-voluntary psychological testing by employers. - Subcommittee chaired by Senator Sam Ervin.

1967

- Hawaii enacted a licensure law for psychology practice.

1990

- First William James Fellow Awards by the American Psychological Society. - Recipients: Frances K. Graham and William K. Estes.

••UNDERSTANDING PSYCHOLOGICAL TESTING••

∆ Classical Test Theory (CTT): Explanation: Classical Test Theory is a basic theory in psychometrics that helps us understand the reliability and validity of psychological tests. It focuses on the idea that each person's test score consists of two parts: the true score (what the person's ability or trait truly is) and measurement error (random fluctuations in the test score). Important Points: A reliable test produces consistent results when administered multiple times to the same individuals. Validity means the test measures what it's supposed to measure accurately. Creator: The origins of CTT can be traced back to several statisticians, including Charles Spearman and Louis Leon Thurstone.