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spline poisson regression model  (STATA Corporation)


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    STATA Corporation spline poisson regression model
    (A ) Numbers of all face-to-face appointments of patients aged ≥75 years to GPs per 1000 person-years. The line shows the mean, and the dashed area the 95% confidence interval. ( B ) Numbers of non-urgent scheduled and urgent scheduled appointments to GPs per 1000 person-years. The appointments were derived from 4-knot-restricted cubic <t>spline</t> <t>regression</t> models. Grey areas represent 95% confidence intervals. pyrs = person-years; 0 = timepoint of <t>model</t> change.
    Spline Poisson Regression Model, supplied by STATA Corporation, used in various techniques. Bioz Stars score: 99/100, based on 35482 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/spline+poisson+regression+model/pmc10646206-60-19-23?v=STATA+Corporation
    Average 99 stars, based on 35482 article reviews
    spline poisson regression model - by Bioz Stars, 2026-06
    99/100 stars

    Images

    1) Product Images from "Comparison of two GP service provider models in older adults: a register-based follow-up study"

    Article Title: Comparison of two GP service provider models in older adults: a register-based follow-up study

    Journal: BJGP Open

    doi: 10.3399/BJGPO.2022.0101

    (A ) Numbers of all face-to-face appointments of patients aged ≥75 years to GPs per 1000 person-years. The line shows the mean, and the dashed area the 95% confidence interval. ( B ) Numbers of non-urgent scheduled and urgent scheduled appointments to GPs per 1000 person-years. The appointments were derived from 4-knot-restricted cubic spline regression models. Grey areas represent 95% confidence intervals. pyrs = person-years; 0 = timepoint of model change.
    Figure Legend Snippet: (A ) Numbers of all face-to-face appointments of patients aged ≥75 years to GPs per 1000 person-years. The line shows the mean, and the dashed area the 95% confidence interval. ( B ) Numbers of non-urgent scheduled and urgent scheduled appointments to GPs per 1000 person-years. The appointments were derived from 4-knot-restricted cubic spline regression models. Grey areas represent 95% confidence intervals. pyrs = person-years; 0 = timepoint of model change.

    Techniques Used: Derivative Assay

    The top figure illustrates the numbers of all face-to-face appointments to GPs per 1000 person-years and the bottom figure the respective amount of GP workforce expressed as person-years adjusted to the number of patients aged ≥75 years. The appointments were derived from 4-knot-restricted cubic spline regression models. Grey areas represent 95% confidence intervals. pyrs = person-years; 0 = timepoint of model change.
    Figure Legend Snippet: The top figure illustrates the numbers of all face-to-face appointments to GPs per 1000 person-years and the bottom figure the respective amount of GP workforce expressed as person-years adjusted to the number of patients aged ≥75 years. The appointments were derived from 4-knot-restricted cubic spline regression models. Grey areas represent 95% confidence intervals. pyrs = person-years; 0 = timepoint of model change.

    Techniques Used: Derivative Assay



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    (A ) Numbers of all face-to-face appointments of patients aged ≥75 years to GPs per 1000 person-years. The line shows the mean, and the dashed area the 95% confidence interval. ( B ) Numbers of non-urgent scheduled and urgent scheduled appointments to GPs per 1000 person-years. The appointments were derived from 4-knot-restricted cubic <t>spline</t> <t>regression</t> models. Grey areas represent 95% confidence intervals. pyrs = person-years; 0 = timepoint of <t>model</t> change.
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    (A ) Numbers of all face-to-face appointments of patients aged ≥75 years to GPs per 1000 person-years. The line shows the mean, and the dashed area the 95% confidence interval. ( B ) Numbers of non-urgent scheduled and urgent scheduled appointments to GPs per 1000 person-years. The appointments were derived from 4-knot-restricted cubic <t>spline</t> <t>regression</t> models. Grey areas represent 95% confidence intervals. pyrs = person-years; 0 = timepoint of <t>model</t> change.
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    Image Search Results


    (A ) Numbers of all face-to-face appointments of patients aged ≥75 years to GPs per 1000 person-years. The line shows the mean, and the dashed area the 95% confidence interval. ( B ) Numbers of non-urgent scheduled and urgent scheduled appointments to GPs per 1000 person-years. The appointments were derived from 4-knot-restricted cubic spline regression models. Grey areas represent 95% confidence intervals. pyrs = person-years; 0 = timepoint of model change.

    Journal: BJGP Open

    Article Title: Comparison of two GP service provider models in older adults: a register-based follow-up study

    doi: 10.3399/BJGPO.2022.0101

    Figure Lengend Snippet: (A ) Numbers of all face-to-face appointments of patients aged ≥75 years to GPs per 1000 person-years. The line shows the mean, and the dashed area the 95% confidence interval. ( B ) Numbers of non-urgent scheduled and urgent scheduled appointments to GPs per 1000 person-years. The appointments were derived from 4-knot-restricted cubic spline regression models. Grey areas represent 95% confidence intervals. pyrs = person-years; 0 = timepoint of model change.

    Article Snippet: A possible non-linear relationship between the number of contacts and the years was assessed by using a 4-knot-restricted cubic spline Poisson regression model. Stata (version 17.0) statistical package was used for the analysis.

    Techniques: Derivative Assay

    The top figure illustrates the numbers of all face-to-face appointments to GPs per 1000 person-years and the bottom figure the respective amount of GP workforce expressed as person-years adjusted to the number of patients aged ≥75 years. The appointments were derived from 4-knot-restricted cubic spline regression models. Grey areas represent 95% confidence intervals. pyrs = person-years; 0 = timepoint of model change.

    Journal: BJGP Open

    Article Title: Comparison of two GP service provider models in older adults: a register-based follow-up study

    doi: 10.3399/BJGPO.2022.0101

    Figure Lengend Snippet: The top figure illustrates the numbers of all face-to-face appointments to GPs per 1000 person-years and the bottom figure the respective amount of GP workforce expressed as person-years adjusted to the number of patients aged ≥75 years. The appointments were derived from 4-knot-restricted cubic spline regression models. Grey areas represent 95% confidence intervals. pyrs = person-years; 0 = timepoint of model change.

    Article Snippet: A possible non-linear relationship between the number of contacts and the years was assessed by using a 4-knot-restricted cubic spline Poisson regression model. Stata (version 17.0) statistical package was used for the analysis.

    Techniques: Derivative Assay