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Tag: regression

What is Confirmatory Factor Analysis?

What is Confirmatory Factor Analysis?

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Confirmatory Factor Analysis (CFA) is a statistical technique used to test and confirm the factor structure of a set of observed variables based on a hypothesized model. Unlike Exploratory Factor Analysis (EFA), which aims to explore and uncover the underlying structure of a dataset, CFA is used to evaluate whether a pre-specified factor model fits the data well. Here’s how confirmatory factor analysis works: Hypothesized Model Specification: Before conducting CFA, researchers specify a theoretical model that represents the relationships among…

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What is Exploratory Factor Analysis?

What is Exploratory Factor Analysis?

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Exploratory Factor Analysis (EFA) is a statistical technique used to uncover the underlying structure or patterns in a dataset, particularly when dealing with a large number of variables. It aims to identify the underlying factors that explain the correlations among observed variables. Here’s how exploratory factor analysis works: Data Preparation: EFA typically begins with a dataset containing multiple observed variables (e.g., survey items, test scores). Factor Extraction: The goal of factor extraction is to identify a smaller number of underlying…

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What is multinomial logistic regression?

What is multinomial logistic regression?

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Multinomial logistic regression is a statistical method used to model the relationship between one or more independent variables and a categorical dependent variable with more than two unordered categories. It is an extension of binary logistic regression to situations where the outcome variable has multiple categories that are not ordered. In multinomial logistic regression, the dependent variable is categorical and nominal, meaning the categories have no natural ordering. Examples of such variables include types of diseases (e.g., cancer types), political…

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What is ordinal logistic regression?

What is ordinal logistic regression?

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Ordinal logistic regression is a statistical method used to model the relationship between one or more independent variables and an ordinal dependent variable. It is an extension of binary logistic regression to situations where the outcome variable has more than two ordered categories but maintains the ordinal nature of the categories. In ordinal logistic regression, the dependent variable is categorical and ordinal, meaning it has a natural ordering but the intervals between categories may not be equal. For example, Likert…

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How do I choose the correct statistical test?

How do I choose the correct statistical test?

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Choosing the correct statistical analysis is crucial for obtaining meaningful and valid results in a research study. Here are some steps to guide you in selecting the appropriate statistical analysis: Define Your Research Question: Clearly articulate your research question or hypothesis. The nature of your question will influence the type of statistical analysis needed. Questions generally fall into one of three types: descriptive, correlational/predictive and cause/effect or experimental. Understand Your Data: Examine the characteristics of your data, including the type…

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What is hierarchical multiple regression?

What is hierarchical multiple regression?

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Hierarchical multiple regression is a statistical method used in regression analysis to explore the relationship between a dependent variable and multiple independent variables while accounting for the influence of different sets of variables in a specific order or hierarchy. The term “hierarchical” indicates that the independent variables are entered into the regression equation in a specific sequence based on theoretical or practical considerations. Here’s a general overview of how hierarchical multiple regression works: Stepwise Entry of Variables: Variables are grouped…

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