Enhance Your Learning with Meta-Analysis in Political Science Flash Cards for quick revision
A statistical technique used to combine and analyze data from multiple studies to draw conclusions and make inferences about a particular research question or hypothesis.
The overall plan or structure of a research study, including the selection of participants, data collection methods, and statistical analysis techniques.
The systematic approach and set of procedures used in a research study, including the selection of research methods, data collection, and data analysis.
The process of gathering information or data from various sources, such as surveys, interviews, or existing datasets, for the purpose of analysis and interpretation.
The process of inspecting, cleaning, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making.
A quantitative measure of the magnitude or strength of the relationship between variables in a study, indicating the practical significance of the findings.
A measure of the probability that an observed effect or relationship in a study is not due to chance, typically determined through hypothesis testing.
The tendency for published research studies to selectively report positive or significant results, leading to an overestimation of the true effect size.
The degree of variability or diversity among the effect sizes of individual studies included in a meta-analysis, indicating potential differences in study characteristics or populations.
An examination of the influence of specific study characteristics or variables on the relationship between the independent and dependent variables in a meta-analysis.
A statistical technique used to explore the relationship between study-level characteristics and effect sizes in a meta-analysis, allowing for the identification of potential moderators.
Computer programs or tools specifically designed for conducting meta-analyses, facilitating data management, effect size calculation, and statistical analysis.
A comprehensive and structured approach to reviewing and summarizing existing research studies on a specific topic, often serving as a foundation for meta-analysis.
Different specialized areas or branches of political science, such as comparative politics, international relations, political theory, public administration, and public policy.
A research approach that focuses on the collection and analysis of numerical data, often using statistical methods to uncover patterns, relationships, and trends.
A research approach that emphasizes the exploration and understanding of complex phenomena through the collection and analysis of non-numerical data, such as interviews, observations, or textual analysis.
An approach that combines both quantitative and qualitative research methods and data, aiming to provide a more comprehensive and nuanced understanding of a research topic.
Methods used to select a subset of individuals or cases from a larger population for inclusion in a research study, ensuring representativeness and generalizability of findings.
Factors or variables that are not the main focus of a study but can influence the relationship between the independent and dependent variables, leading to spurious or misleading results.
The process of determining whether a causal relationship exists between two or more variables, often through the use of experimental or quasi-experimental designs.
The principles and guidelines that govern the ethical conduct of research, ensuring the protection of participants' rights, privacy, and well-being.
A critical evaluation and synthesis of existing research studies and scholarly articles on a specific topic, providing a comprehensive overview of the current state of knowledge.
A statement or assumption that there is no significant relationship or difference between variables in a study, which is tested against an alternative hypothesis.
A statement or assumption that there is a significant relationship or difference between variables in a study, which is tested against a null hypothesis.
A range of values within which the true population parameter is estimated to lie with a certain level of confidence, often expressed as a percentage.
A measure of the strength of evidence against the null hypothesis in a statistical test, indicating the probability of obtaining the observed results by chance alone.
A false positive error that occurs when the null hypothesis is rejected, indicating a significant relationship or difference between variables when there is none in the population.
A false negative error that occurs when the null hypothesis is not rejected, indicating no significant relationship or difference between variables when there is one in the population.
A statistical technique used to determine the sample size needed to detect a significant effect or relationship between variables with a desired level of power.
A situation in which the relationship between two variables is modified or influenced by the presence of a third variable, leading to different effects or associations.
The principles and guidelines that govern the ethical conduct of publishing research, ensuring the integrity, transparency, and credibility of scientific knowledge.
An international network of researchers, professionals, and organizations dedicated to producing and disseminating high-quality systematic reviews and meta-analyses in various fields, including political science.
A graphical representation of the effect sizes and confidence intervals of individual studies included in a meta-analysis, providing a visual summary of the overall findings.
A graphical tool used to assess the presence of publication bias in a meta-analysis, plotting the effect sizes against their standard errors or sample sizes.
A statistical technique used to assess the robustness and reliability of the results of a meta-analysis by systematically varying the inclusion criteria or analytical methods.
A statistical model used in meta-analysis that assumes the effect sizes of individual studies are not identical but vary due to both sampling error and true heterogeneity.
A statistical model used in meta-analysis that assumes the effect sizes of individual studies are identical and any observed differences are due to sampling error alone.
The process of assigning different weights or importance to the effect sizes of individual studies in a meta-analysis, often based on sample size or study quality.
The calculation or estimation of the magnitude or strength of the relationship between variables in a study, often expressed as a standardized measure.
A type of bias that occurs when an extraneous variable or factor is associated with both the independent and dependent variables, leading to a spurious or misleading relationship.
The possibility that unpublished or non-significant studies with null or negative results are not included in a meta-analysis, leading to an overestimation of the true effect size.
A type of bias that occurs when studies with positive or significant results are more likely to be cited and included in a meta-analysis, leading to an overestimation of the true effect size.
The systematic evaluation and appraisal of the methodological quality, validity, and reliability of individual studies included in a meta-analysis.
The guidelines and criteria set by academic journals and publishers for the acceptance and publication of research studies, ensuring scientific rigor and integrity.
The ability of other researchers to replicate or reproduce the results of a research study using the same data, methods, and procedures.
The openness and accessibility of research data, methods, and findings, allowing for scrutiny, verification, and replication by the scientific community.
The process of systematically combining and integrating the findings of multiple research studies on a specific topic to generate new insights, identify patterns, and draw conclusions.
The extent to which a research study measures what it intends to measure and accurately reflects the underlying construct or phenomenon of interest.
The consistency and stability of the results of a research study, indicating the degree to which the findings can be replicated or reproduced under similar conditions.
Systematic errors or deviations from the truth or accuracy in the design, conduct, or reporting of a research study, leading to invalid or unreliable results.
The adherence to ethical and professional standards in the design, conduct, and reporting of research, ensuring honesty, transparency, and accountability.