Statistical Distributions of Daily Breathing Rates for Narrow Age Groups of Infants and Children

Children may be more susceptible to toxicity from some environmental chemicals than adults. This susceptibility may occur during narrow age periods (windows), which can last from days to years depending on the toxicant. Breathing rates specific to narrow age periods are useful to assess inhalation dose during suspected windows of susceptibility. Because existing breathing rates used in risk assessment are typically for broad age ranges or are based on data not representative of the population, we derived daily breathing rates for narrow age ranges of children designed to be more representative of the current U.S. children's population. These rates were derived using the metabolic conversion method of Layton (1993) and energy intake data adjusted to represent the U.S. population from a relatively recent dietary survey (CSFII 1994–1996, 1998). We calculated conversion factors more specific to children than those previously used. Both nonnormalized (L/day) and normalized (L/kg-day) breathing rates were derived and found comparable to rates derived using energy estimates that are accurate for the individuals sampled but not representative of the population. Estimates of breathing rate variability within a population can be used with stochastic techniques to characterize the range of risk in the population from inhalation exposures. For each age and age-gender group, we present the mean, standard error of the mean, percentiles (50th, 90th, and 95th), geometric mean, standard deviation, 95th percentile, and best-fit parametric models of the breathing rate distributions. The standard errors characterize uncertainty in the parameter estimate, while the percentiles describe the combined interindividual and intra-individual variability of the sampled population. These breathing rates can be used for risk assessment of subchronic and chronic inhalation exposures of narrow age groups of children.     

Intersensory Redundancy Enhances Memory in Bobwhite Quail Embryos

Information presented concurrently and redundantly to 2 or more senses (intersensory redundancy) has been shown to recruit attention and promote perceptual learning of amodal stimulus properties in animal embryos and human infants. This study examined whether the facilitative effect of intersensory redundancy also extends to the domain of memory. We assessed bobwhite quail chicks' ability to remember and prefer an individual maternal call presented either unimodally or redundantly and synchronously with patterned light during the period prior to hatching. Embryos provided with unimodal auditory exposure failed to prefer the familiar call over a novel maternal call postnatally at 48 hr and 72 hr following exposure. In contrast, embryos provided with redundant, synchronous audiovisual stimulation significantly preferred the familiar call at 48 hr following exposure, but not at 72 hr. A second experiment provided chicks with a single 10‐min refamiliarization with the familiar call at either 48 hr or 72 hr following hatching. Chicks given only unimodal auditory exposure prior to hatching did not appear to benefit from this brief postnatal refamiliarization, showing no preference for the familiar call at either 72 or 96 hr. Chicks that received redundant audiovisual stimulation prenatally showed a significant preference for the familiar call (following the brief reexpo sure 24 hr earlier) at both 72 and 96 hr of age. These results are the first to demonstrate that redundantly specified information is remembered longer and reactivated more easily than the same information presented unimodally. These findings provide further evidence of the salience of intersensory redundancy in guiding selective attention and perceptual learning during early development.     

Consumption and Saving Behavior of Older and Younger Baby Boomers in Korea

The 1998 Korean Survey of Family Income and Expenditures was used to examine the overall consumption and saving behavior of Korean baby boomers and compared the differences in consumption and saving behavior between older and younger boomers. The t -test results indicated that the younger boomers allocated a significantly higher percentage of their expenditures on food away from home, household appliances, transportation and communication than did the older boomers, whereas the older boomers spent higher amounts and allocated larger budget shares on their children's education than did the younger boomers. The results of Ordinary Least-Squares (OLS) regression analysis showed that, holding other factors constant, older boomers not only spent significantly more in the total consumption expenditures and education expenditures, but older boomers also saved significantly less than did younger boomers.     

Automobile prices and protection: The U.S.-Japan trade restraint

We examine the effects of the U.S.-Japan trade restraint on automobile prices and quality upgrading, for both Japanese imports and American small cars. From April 1981 to April 1984 the suggested retail price of all Japanese models increased by 15.8 percent, or 5.3 percent per year. We find that nearly the entire amount of this rise can be explained by the upgrading of individual models. This upgrading may benefit consumers who would purchase a luxury import in any case, but harms those who desire the basic imports. In addition to upgrading, we conclude that a second cost of the trade restraint has been to prevent the yen depreciation from being passed onto American consumers, in terms of lower imported auto prices. For U.S. small cars we find a 9.1 percent rise in the suggested retail price, or 3 percent per year, with a fraction of this amount due to model upgrading. If the yen depreciation had led to lower import prices without the trade restraint, then we expect that U.S. auto prices would have been lower, too.     

Expectations, Capital Gains, and Income

A theoretical framework for the measurement of income under uncertainty is developed that addresses some long-standing controversies about the treatment of capital gains. The consequences for economic analysis and policy making are potentially serious, because the treatment of capital gains can significantly affect some major macroeconomic aggregates, including national income and savings, balance of payments deficits, government deficits, and depreciation. (JEL O47 , P44 , Q32 )     

Choice of the primary analysis in longitudinal clinical trials

Missing data, and the bias they can cause, are an almost ever‐present concern in clinical trials. The last observation carried forward (LOCF) approach has been frequently utilized to handle missing data in clinical trials, and is often specified in conjunction with analysis of variance (LOCF ANOVA) for the primary analysis. Considerable advances in statistical methodology, and in our ability to implement these methods, have been made in recent years. Likelihood‐based, mixed‐effects model approaches implemented under the missing at random (MAR) framework are now easy to implement, and are commonly used to analyse clinical trial data. Furthermore, such approaches are more robust to the biases from missing data, and provide better control of Type I and Type II errors than LOCF ANOVA. Empirical research and analytic proof have demonstrated that the behaviour of LOCF is uncertain, and in many situations it has not been conservative. Using LOCF as a composite measure of safety, tolerability and efficacy can lead to erroneous conclusions regarding the effectiveness of a drug. This approach also violates the fundamental basis of statistics as it involves testing an outcome that is not a physical parameter of the population, but rather a quantity that can be influenced by investigator behaviour, trial design, etc. Practice should shift away from using LOCF ANOVA as the primary analysis and focus on likelihood‐based, mixed‐effects model approaches developed under the MAR framework, with missing not at random methods used to assess robustness of the primary analysis. Copyright © 2004 John Wiley & Sons, Ltd.     

Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix

Approximation formulae are developed for the bias of ordinary and generalized Least Squares Dummy Variable (LSDV) estimators in dynamic panel data models. Results from Kiviet [Kiviet, J. F. (1995), on bias, inconsistency, and efficiency of various estimators in dynamic panel data models, J. Econometrics68:53-78; Kiviet, J. F. (1999), Expectations of expansions for estimators in a dynamic panel data model: some results for weakly exogenous regressors, In: Hsiao, C., Lahiri, K., Lee, L-F., Pesaran, M. H., eds., Analysis of Panels and Limited Dependent Variables, Cambridge: Cambridge University Press, pp. 199-225] are extended to higher-order dynamic panel data models with general covariance structure. The focus is on estimation of both short- and long-run coefficients. The results show that proper modelling of the disturbance covariance structure is indispensable. The bias approximations are used to construct bias corrected estimators which are then applied to quarterly data from 14 European Union countries. Money demand functions for M1, M2 and M3 are estimated for the EU area as a whole for the period 1991: I-1995: IV. Significant spillovers between countries are found reflecting the dependence of domestic money demand on foreign developments. The empirical results show that in general plausible long-run effects are obtained by the bias corrected estimators. Moreover, finite sample bias, although of moderate magnitude, is present underlining the importance of more refined estimation techniques. Also the efficiency gains by exploiting the heteroscedasticity and cross-correlation patterns between countries are sometimes considerable.