Related Experiment Video

Updated: Jun 5, 2026

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI)
06:26

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI)

Published on: November 27, 2019

[Methods of statistical analysis in psychiatric publications]

A A Ivushkin, A V Nemtsov

    Zhurnal Nevrologii I Psikhiatrii Imeni S.S. Korsakova
    |December 25, 2010
    PubMed

    Related Concept Videos

    Statistical Methods for Analyzing Epidemiological Data01:25

    Statistical Methods for Analyzing Epidemiological Data

    Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
    Statistical Methods to Analyze Parametric Data: ANOVA01:12

    Statistical Methods to Analyze Parametric Data: ANOVA

    Analysis of Variance, or ANOVA, is a powerful statistical technique used to analyze parametric data, primarily in research and experimental studies. It's designed to compare the means of two or more groups, assisting researchers in identifying any significant differences between these group means. There are two main types of ANOVA based on the complexity of the analysis: one-way and two-way.
    One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares the...
    Statistical Software for Data Analysis and Clinical Trials01:12

    Statistical Software for Data Analysis and Clinical Trials

    Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
    Regression Toward the Mean01:52

    Regression Toward the Mean

    Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
    Chi-square Analysis02:46

    Chi-square Analysis

    The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
    The chi-square test was developed by Pearson in 1990.
    The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
    Statistical Significance01:37

    Statistical Significance

    Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...