Related Experiment Video

Updated: Sep 30, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

[Application of polychotomous logistic regression in the study of risk factors predisposed to postpartum hemorrhage]

H Ni, G Zhang

    Hua Xi Yi Ke Da Xue Xue Bao = Journal of West China University of Medical Sciences = Huaxi Yike Daxue Xuebao
    |September 1, 1991
    PubMed

    To determine the role of history of induced abortion and pregnancy induced hypertension in postpartum hemorrhage, a polychotomous logistic regression method was introduced to analyze the data gathered in an investigation of blood loss among 933 parturients in some counties of Sichuan and Ningxia provinces. The results show that postpartum hemorrhage caused by placenta factors is related to a history of induced abortion and pregnancy induced hypertension with relative risks 2.55 (95% confidence interval = 1.2-5.3) and 4.94 (95% confidence interval = 1.8-13.2), respectively. An increased risk was noted for postpartum hemorrhage associated with pregnancy induced hypertension (relative risk = 2.58, 95% confidence interval = 1.3-5.2), but not with induced abortion. Suggestions were made for prevention of postpartum hemorrhage.

    Related Concept Videos

    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...
    Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

    Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

    Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
    Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
    Odds Ratio01:09

    Odds Ratio

    The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
    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:
    Comparing the Survival Analysis of Two or More Groups01:20

    Comparing the Survival Analysis of Two or More Groups

    Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...
    The Mantel-Cox Log-Rank Test01:19

    The Mantel-Cox Log-Rank Test

    The Mantel-Cox log-rank test is a widely used statistical method for comparing the survival distributions of two groups. It tests whether a statistically significant difference exists in survival times between the groups without assuming a specific distribution for the survival data, making it a non-parametric test. This flexibility makes the log-rank test particularly valuable in medical research and other fields where the timing of an event, such as death or disease recurrence, is of interest.