Addressing the Large Standard Error of Traditional CBM-R: Estimating the Conditional Standard Error of a Model-Based Estimate of CBM-R

Curriculum-based measurement of oral reading fluency (CBM-R) is widely used across the country as a quick measure of reading proficiency that also serves as a good predictor of comprehension and overall reading achievement, but has several practical and technical inadequacies, including a large standard error of measurement (SEM). Reducing the SEM of CBM-R scores has positive implications for educators using these measures to screen or monitor student growth. The purpose of this study was to compare the SEM of traditional CBM-R words correct per minute (WCPM) fluency scores and the conditional SEM (CSEM) of model-based WCPM estimates, particularly for students with or at risk of poor reading outcomes. We found (a) the average CSEM for the model-based WCPM estimates was substantially smaller than the reported SEMs of traditional CBM-R systems, especially for scores at/below the 25th percentile, and (b) a large proportion (84%) of sample scores, and an even larger proportion of scores at/below the 25th percentile (about 99%) had a smaller CSEM than the reported SEMs of traditional CBM-R systems.

Effect of Exclusion of Anomalous Tropical Stations on Temperature Trends from a 63-Station Radiosonde Network, and Comparison with Other Analyses

A 63-station radiosonde network has been used for many years to estimate temperature variations and trends at the surface and in the 850–300-, 300–100-, and 100–50-mb layers of climate zones, both hemispheres, and the globe, but with little regard for the quality of individual station data. In this paper, nine tropical radiosonde stations in this network are identified as anomalous based on unrepresentatively large standard-error-of-regression values for 300–100-mb trends for the period 1958–2000. In the Tropics the exclusion of the 9 anomalous stations from the 63-station network for 1958–2000 results in a warming of the 300–100-mb layer rather than a cooling, a doubling of the warming of the 850–300-mb layer to a value of 0.13 K decade−1, and a greater warming at 850–300-mb than at the surface. The global changes in trend are smaller, but include a change to the same warming of the surface and the 850–300-mb layer during 1958–2000. The effect of the station exclusions is much less for 1979–2000, suggesting that most of the data problems are before this time. Temperature trends based on the 63-station network are compared with the Microwave Sounding Unit (MSU) and other radiosonde trends, and agreement is better after the exclusion of the anomalous stations. There is consensus that in the Tropics the troposphere has warmed slightly more than the surface during 1958–2000, but that there has been a warming of the surface relative to the troposphere during 1979–2000. Globally, the warming of the surface and the troposphere are essentially the same during 1958–2000, but during 1979–2000 the surface warms more than the troposphere. During the latter period the radiosondes indicate considerably more low-stratospheric cooling in the Tropics than does the MSU.

Body composition assessment in lean and normal-weight young women

Using percentage body fat (BF%) from a three-compartment (3C) model (body density from underwater weighing (UWW) and bone-mineral mass from dual-energy X-ray absorptiometry (DXA)) as a criterion, we studied the accuracy of UWW, DXA, two skinfold equations, and two bioimpedance (BIA) equations. Thirty-four women (aged 16–20 years) with BF% 13·5–31·1 volunteered. UWW underestimated BF% by −0·5 BF% (95 % CI: −1·0; −0·02), whereas DXA overestimated it by 7·3 BF% (95% CI5.8;8·8). Skinfolds underestimated and BIA overpredicted BF%. The differences between 3C and UWW, skinfolds (Durnin & Womersley, 1974) and BIA (Deurenberg et al. 1990) were dependent (range of r values: −0.63 to −0.79; P < 0·0001) on BF%, causing an overestimation of lean subjects' (UWW, BIA) or an underestimation of normal-weight subjects' (UWW, skinfolds) BF%. The 3C model and UWW gave comparable body-composition results for healthy young women with BF% of approximately 20–25. Based on a significant mean difference from the 3C model, and a large standard error of the estimate, we do not regard DXA as superior to skinfolds or BIA to assess BF%.

Constrained empirical Bayes estimates for cell values in a two-way table

It is common to summarize the results of a forest inventory in two-way tables. Unfortunately, while the overall sample size may be large, the sample size for an individual cell in the table may be quite small. Thus the estimate may have a large standard error. We propose a simultaneous estimation method to reduce the variance and (or) mean squared error of individual cell estimates while retaining table additivity, i.e., preserving the observed row and column sums of the table.

Ultrasonography for Fetal Weight Estimation: The Birnholz Equation

In the population of 563 normal live births, subject to the selection criteria of this study, the mean ultrasonographically-estimated fetal weight calculated using the Birnholz equation accurately predicts the mean true birth weight with less than 1 percent error. However, on a pairwise basis, the error was found to be systematic (rather than random) with a large standard error of the estimate (± 300 g). The equation consistently underestimated the mean birth weight between 1500–3750 g and consistently overestimated it thereafter.

The Fitness of the Human Zygote

SummaryThe fitness of human zygotes depends on both biological and demographic parameters. Some of the demographic parameters are changing at present in this country and accurate estimates of them are not available but this imprecision has no great bearing on the estimate of fitness offered below.Of 100 human zygotes, now, in this country, it is estimated that embryonic and early fetal loss (before the end of the 3rd month) accounts for 44; induced abortion, 7; late fetal loss (after the 3rd month), 4; and mortality between birth and maturity, 1½. Of the remaining 43½ who reach maturity, it is estimated that 8 fail to reproduce, leaving 35½ who do reproduce.The standard error of this estimate must be large because of the large standard error of the estimate of the incidence of natural reproductive wastage from which it was derived.

RELATIONSHIPS BETWEEN SOIL PHYSICAL CONSTANTS AND SOIL PHYSICAL COMPONENTS OF SOME MANITOBA SOILS

The relationships between soil physical constants and soil components of Manitoba soils were investigated on 112 samples varying widely m physical composition. The physical constants bulk density, field capacity, permanent wilting percentage, available moisture on a weight basis, and available moisture on a volume basis were related to the soil components fine sand, very fane sand, silt, clay, organic matter and calcium carbonate. The results showed that a highly significant relationship existed between soil components and each soil physical constant. In the case of bulk density, field capacity and permanent wilting percentage, the relationships were sufficiently close to permit their use for prediction purposes. The large standard error of estimate for the regression equations of the other two soil physical constants limited their usefulness for this purpose.

The relationship between concentrations of plasma and hepatic vitamin A in steers intensively finished on high-grain rations low in carotene

Data on plasma and liver vitamin A concentrations were obtained from 84 Hereford steers approximately two years of age and approximately 900 lb in body-weight. The animals were sampled from two experiments : 57 received high-grain rations low in carotene for 150 � 15 days, 27 received similar rations for 154 � 6 days. Plasma vitamin A levels in 18 animals were below 20 �g/100 ml, and these values were associated with hepatic levels of less than 10 �g/g. The regression of plasma vitamin A on the logarithm of liver vitamin A was significant (P<0.01) and the regression coefficients were not significantly different between experiments. The equation was y = -30.506 + 19.705 log x. This equation has only limited value for prediction over the whole range tested due to the large standard error (9.24) and the limited magnitude of the correlation coefficient (0.80).