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Tag: inferential

What are common methods used to measure clinical significance?

What are common methods used to measure clinical significance?

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Common measures of clinical significance are used to evaluate the practical importance or relevance of research findings in clinical practice or real-world settings. These measures focus on assessing the magnitude of the effect, its impact on patient outcomes, and its relevance to healthcare decision-making. Here are some common measures of clinical significance: Effect Size: Effect size quantifies the magnitude of the observed effect or difference between groups. Common effect size measures include Cohen’s d for means comparison, odds ratio for…

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What is the difference between statistical and clinical significance?

What is the difference between statistical and clinical significance?

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Statistical significance and clinical significance are two distinct concepts used to interpret research findings, particularly in the context of medical and clinical research. Here’s the difference between the two: Statistical Significance: Statistical significance refers to the likelihood that an observed result is not due to random chance but rather reflects a true effect or relationship in the population. In statistical terms, it indicates whether the results obtained in a study are unlikely to have occurred by random variability alone. Statistical…

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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 are inferential statistics and how are they used?

What are inferential statistics and how are they used?

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Inferential statistics allow us to make decisions about a large group (usually referred to as a population) based upon observations made within a small group selected from that population (usually referred to as a sample. This ability to infer something about a population based upon a sample allows a deeper understanding of data beyond what descriptive statistics alone can offer. Sometimes knowing the mean of a group of scores is enough information. Still, inferential statistics allows us to compare the…

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