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Biomedical subjects

T L Lai

Publications and source records attributed to T L Lai.

26 records · Page 2Linked to original sources

Heart rate and heart rate variability during sleep in aborted sudden infant death syndrome.

Heart rate and heart rate variability were studied during sleep at monthly intervals in 18 normal infants and 12 infants with aborted sudden infant death syndrome during the first four months of life. At each age studied and in both REM and quiet sleep, the aborted SIDS infants had a 5 to 10% faster heart rate. Moreover, the aborted SIDS infants had a 10 to 45% smaller beat-to-beat and overall heart rate variability. Although the differences in overall variability persisted after normalization by the absolute heart rate, the differences in the beat-to-beat variability narrowed. These findings, when taken in conjunction with our previous observation that aborted SIDS infants have a smaller QT index than normal infants, suggest that infants with aborted SIDS have an increase in sympathetic activity or in circulating levels of catecholamines.

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Sequential medical trials.

A model for sequential clinical trials is discussed. Three proposed stopping rules are studied by the Monte Carlo method for small patient horizons and mathematically for large patient horizons. They are shown to be about equally effective and asymptotically optimal from both Bayesian and frequentist points of view and are markedly superior to any fixed sample size procedure.

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Local convergence theorems for adaptive stochastic approximation schemes.

For the regression model y = M(x) + epsilon, adaptive stochastic approximation schemes of the form x(n+1) = x(n) - y(n)/(nb(n)) for choosing the levels x(1),x(2),... at which y(1),y(2),... are observed converge with probability 1 to the unknown root theta of the regression function M(x). Certain local convergence theorems that relate the convergence rate of x(n) - theta to the limiting behavior of the random variables b(n) are established.

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Adaptive design in regression and control.

When y = M(x) + epsilon, where M may be nonlinear, adaptive regression designs of the levels x(1), x(2),... at which y(1), y(2),... are observed lead to asymptotically efficient estimates of the value theta of x for which M(theta) is equal to any desired value y(*). More importantly, these designs also make the "cost" of the observations, defined at the nth stage to be Sigma(1) (n) (x(i) - theta)(2), to be of the order of log n instead of n, an obvious advantage in medical and other applications.

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Strong consistency of least-squares estimates in regression models.

A general theorem on the limiting behavior of certain weighted sums of i.i.d. random variables is obtained. This theorem is then applied to prove the strong consistency of least-squares estimates in linear and nonlinear regression models with i.i.d. errors under minimal assumptions on the design and weak moment conditions on the errors.

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Maximally dependent random variables.

Let X(1),..., X(n) have an arbitrary common marginal distribution function F, and let M(n) = max(X(1),..., X(n)). It is shown that EM(n) </= m(n), where m(n) = a(n) + n[unk](an) (infinity)[1 -F(x)]dx and = F(-1)(1 - n(-1)), and that EM(n) = m(n) when X(1),..., X(n) are "maximally dependent"; i.e., P(M(n) > x) = min{1, n[1 - F(x)]} for all x. Moreover, as n --> infinity, a(n) approximately m(n) approximately m(n) (*), where m(n) (*) = EM(n) when X(1),..., X(n) are independent, provided that [1 - F(cx)]/[1 - F(x)] --> 0 as x --> infinity for every c > 1, and E(X(1) (-))(r) < infinity for some r > 0. The case in which F is standard normal is considered in detail.

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