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  • 1
    In: European Journal of Endocrinology, Oxford University Press (OUP), Vol. 189, No. 2 ( 2023-08-02), p. 183-189
    Abstract: Research suggests that postnatal catch-up growth after fetal growth restriction (FGR) occurs frequently. Yet, postnatal growth in singletons may be influenced by multiple factors. Identical twins with discordant prenatal growth, termed selective FGR (sFGR), can be regarded as a natural experiment eliminating these sources of bias. Design Observational cohort study. Methods Monochorionic twins with sFGR born between 2002 and 2017 (aged 3-17 years) were eligible. Growth measurements (height, weight, head circumference, and body mass index) were performed at follow-up. Detailed growth curves documented by a systematic primary care system in the Netherlands were collected. Measurements were converted to standard deviation scores (SDSs). A mixed-effects model was used to assess within-pair SDS difference and individual height SDS relative to target height SDS. Results Forty-seven twin pairs (94 children) were included at a median age of 11 (interquartile range 8-13) years. At the last measurement, smaller twins at birth had a lower height SDS [−0.6 vs −0.3, P & lt; .001, median difference 0.5 (95%CI 0.4-0.7)], lower weight SDS [−0.5 vs −0.1, P & lt; .001, median difference 0.8 (95%CI 0.5-1.0)], and lower head circumference SDS [−0.5 vs 0.2, P & lt; .001, median difference 0.8 (95%CI 0.6-0.9)] compared to larger twins. These differences persisted until the age of 17. Smaller twins showed rapid catch-up growth in the first 2 years and reached their target height range between 8 and 11 years. Conclusions Identical twins with discordant prenatal growth maintain a modest but significant difference in height, weight, and head circumference, indicating a persistent, inhibitory effect of an adverse intrauterine environment on childhood growth.
    Type of Medium: Online Resource
    ISSN: 0804-4643 , 1479-683X
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    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 1485160-X
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  • 2
    In: Journal of Biomechanics, Elsevier BV, Vol. 63 ( 2017-10), p. 192-196
    Type of Medium: Online Resource
    ISSN: 0021-9290
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    Language: English
    Publisher: Elsevier BV
    Publication Date: 2017
    detail.hit.zdb_id: 1498351-5
    SSG: 12
    SSG: 31
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  • 3
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2020
    In:  Biometrika Vol. 107, No. 3 ( 2020-09-01), p. 677-688
    In: Biometrika, Oxford University Press (OUP), Vol. 107, No. 3 ( 2020-09-01), p. 677-688
    Abstract: We present a new general method for constrained likelihood ratio testing which, when few constraints are violated, improves upon the existing approach in the literature that compares the likelihood ratio with the quantile of a mixture of chi-squared distributions; the improvement is in terms of both simplicity and power. The proposed method compares the constrained likelihood ratio statistic against the quantile of only one chi-squared random variable with data-dependent degrees of freedom. The new test is shown to have a valid exact significance level $\alpha$. It also has more power than the classical approach against alternatives for which the number of violations is not large. We provide more details for testing a simple order $\mu_1\leqslant\cdots\leqslant\mu_p$ against all alternatives using the proposed approach and give clear guidelines as to when the new method would be advantageous. A simulation study suggests that for testing a simple order, the new approach is more powerful in many scenarios than the existing method that uses a mixture of chi-squared variables. We illustrate the results of our adaptive procedure using real data on the liquidity preference hypothesis.
    Type of Medium: Online Resource
    ISSN: 0006-3444 , 1464-3510
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    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 1119-8
    detail.hit.zdb_id: 1470319-1
    SSG: 12
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  • 4
    Online Resource
    Online Resource
    Wiley ; 2022
    In:  Biometrics Vol. 78, No. 1 ( 2022-03), p. 238-247
    In: Biometrics, Wiley, Vol. 78, No. 1 ( 2022-03), p. 238-247
    Abstract: When a ranking of institutions such as medical centers or universities is based on a numerical measure of performance provided with a standard error, confidence intervals (CIs) should be calculated to assess the uncertainty of these ranks. We present a novel method based on Tukey's honest significant difference test to construct simultaneous CIs for the true ranks. When all the true performances are equal, the probability of coverage of our method attains the nominal level. In case the true performance measures have no exact ties, our method is conservative. For this situation, we propose a rescaling method to the nominal level that results in shorter CIs while keeping control of the simultaneous coverage. We also show that a similar rescaling can be applied to correct a recently proposed Monte‐Carlo based method, which is anticonservative. After rescaling, the two methods perform very similarly. However, the rescaling of the Monte‐Carlo based method is computationally much more demanding and becomes infeasible when the number of institutions is larger than 30–50. We discuss another recently proposed method similar to ours based on simultaneous CIs for the true performance. We show that our method provides uniformly shorter CIs for the same confidence level. We illustrate the superiority of our new methods with a data analysis for travel time to work in the United States and on rankings of 64 hospitals in the Netherlands.
    Type of Medium: Online Resource
    ISSN: 0006-341X , 1541-0420
    URL: Issue
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    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2054197-1
    SSG: 12
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