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Related Concept Videos

What are Estimates?01:06

What are Estimates?

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It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
The estimate for the mean of a sample is denoted by ͞x, whereas the mean of the population is designated as μ. Further, parameters such...
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Stereotypes, Prejudice, and Discrimination02:55

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Humans are very diverse and although we share many similarities, we also have many differences. The social groups we belong to help form our identities (Tajfel, 1974). These differences may be difficult for some people to reconcile, which may lead to prejudice toward people who are different. Prejudice is a negative attitude and feeling toward an individual based solely on one’s membership in a particular social group (Allport, 1954; Brown, 2010). Prejudice is common against people who...
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Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
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The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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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:
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Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
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When Race/Ethnicity Data Are Lacking: Using Advanced Indirect Estimation Methods to Measure Disparities.

Allen Fremont, Joel S Weissman, Emily Hoch

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    New methods estimate race/ethnicity using surnames and neighborhood data to help reduce health care disparities. These probabilistic estimates improve monitoring of care quality and utilization for all Americans.

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    Area of Science:

    • Health Services Research
    • Health Equity
    • Biostatistics

    Background:

    • US healthcare reforms aim for equitable care and improved quality for all.
    • Limited race/ethnicity data in health records hinders efforts to achieve health equity.
    • Persistent gaps in healthcare access and quality exist, especially for minority and low-income groups.

    Purpose of the Study:

    • To describe indirect estimation methods for producing probabilistic race/ethnicity data.
    • To enable monitoring of healthcare utilization and quality improvement.
    • To address barriers in routine monitoring and action to reduce health disparities.

    Main Methods:

    • Utilized indirect estimation techniques to generate probabilistic race/ethnicity populations.
    • Employed Bayesian Indirect Surname Geocoding (BISG).
    • BISG uses Census surname data and neighborhood racial/ethnic composition to estimate individual probabilities of belonging to specific racial/ethnic groups.

    Main Results:

    • Developed and described methods for probabilistic race/ethnicity estimation.
    • These methods overcome limitations of incomplete race/ethnicity data in healthcare records.
    • Advances enable health plans and organizations to monitor and address care disparities.

    Conclusions:

    • Probabilistic race/ethnicity estimation methods are crucial for advancing health equity.
    • These techniques facilitate routine monitoring and targeted interventions to reduce disparities.
    • Further guidance is needed to effectively apply these new data for disparity reduction.