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Biomedical subjects

E D Schneiderman

Publications and source records attributed to E D Schneiderman.

At least 19 recordsLinked to original sources
PubMed2001

A performance examination for assessing dental hygiene competencies.

A performance assessment was developed to assess multiple skills from a new competency document. Faculty members developed the tasks that each student would perform, the evaluation criteria, and the testing procedures. Grant project leaders consolidated these materials into the Senior Exit Examination (SEE). The 11 tasks included interpreting a research article, solving an ethical dilemma, and developing a community intervention. An objective, structured clinical examination had stations for interpreting radiographs, describing oral lesions, taking vital signs, taking and analyzing health histories, and communicating with "difficult" patients. Pilot administration of the SEE was conducted in April 1995 and 1996. The majority of the students passed 4 of the 11 tasks on the first attempt in 1995, and 7 passed in 1996. Following changes to the exam and the curriculum, the SEE was conducted four times from 1997 to 2000. Student performance for all tasks in 2000 was at the approximate level of > or = 80% pass rate. Pearson chi-square tests showed that student performance significantly improved over the years from 1995 to 2000 for 9 of the 11 tasks (p < 0.001); a high performance level was maintained in ethics and community intervention with no significant change. The SEE is now considered an important measure for assessing student competence and program outcomes.

Chi-Square Distribution↗
PubMed1995

PC program for assessing the effect of a treatment when subjects are growing: comparative studies.

We describe, illustrate, and make available a menu-driven PC program which can be used to assess the effect of a treatment on growth when random allocation of subjects to the treatment and control groups is not feasible. Three different estimators of, and confidence intervals for, this effect are computed, namely, the simple gains, standardized gains, and covariance adjusted estimators. It is shown by means of several examples that these estimators can differ substantially, and some guidelines for choosing between them in specific circumstances are provided.

Analysis of Variance↗
PubMed1995

PC program for determining the dose necessary to produce a given amount of change.

Given a simple linear regression equation of the form D = alpha + beta Z, it is well-known how to predict, and construct confidence intervals for, the value of D corresponding to a given Z. In this paper we describe, illustrate and make available a menu-driven PC program which can be used to solve the inverse problem, namely, to estimate and construct confidence intervals for the value of Z corresponding to a given value of D. We describe the procedure in the context of a dose-response relationship, where it is desired to estimate the dose (Z) to effect a given amount of change (D), but the method is more general than this. In particular, it may be usefully applied in calibration problems where one may wish to estimate the true value of a measurement given the value as read from a measuring device.

Antimony↗
PubMed1995

PC program for simultaneously testing equality of means and variances for paired bivariate normal data.

A menu-driven PC program for simultaneously testing the equality of means and variances for paired bivariate normal data is described, illustrated and made available. While the corresponding tests for independent samples are well-known and widely implemented, in the paired situation only the test for no change in mean values (the paired t-test) has been similarly covered. Tests for no change in variability, while important, are less well-known and not implemented in most commercial statistical computing programs.

Analysis of Variance↗
PubMed1995

PC program extending the Potthoff-Roy longitudinal data analysis model to allow missing data: Kleinbaum's method.

Potthoff and Roy (Biometrika, 51 (1964) 313-326) generalized the multivariate analysis of variance model into a form that is especially useful for the study of longitudinal growth curve data. Applications of this method have, however, been limited by the requirement that each case in the sample be measured at the same set of time points, i.e. there can be no missing data. In this paper we describe, illustrate, and make available a user-friendly, interactive PC program implementing Kleinbaum's (J Mult Anal, 3 (1973) 117-124) extension of the Potthoff-Roy model to allow incomplete measurement sequences. These missing data are permitted to arise either randomly or by design as in mixed longitudinal studies.

Analysis of Variance↗
PubMed1995

Program assessment practices in dental hygiene education.

A survey asked U.S. dental hygiene program directors to describe their assessment programs and satisfaction with these programs. A 65 percent response rate (138/212) resulted. The directors were less than satisfied with their assessment practices and how they use their assessment data. The majority use alumni (78 percent) and employer (61 percent) surveys and curriculum evaluations by students (57 percent). Fewer use patient satisfaction surveys (40 percent) and exit interviews (33 percent). Only 35 percent of the programs formally validate any instruments. They share the results with faculty (92 percent) but not students (42 percent) and alumni (25 percent). They use the data for curriculum revision (84 percent) but not for adding assessment measures (26 percent), remediation of students (25 percent), or gaining resources for the program (22 percent). Dental hygiene education needs a more comprehensive assessment model that is clearly linked to improvement.

Dental Hygienists↗
PubMed1994

A PC program for classification into one of several groups on the basis of longitudinal data.

A stand-alone, menu-driven PC program, ZCLASS, written in GAUSS386i, for classifying subjects into one of several distinct, existing groups on the basis of longitudinal data is described, illustrated, and made available to interested readers. The program accepts data from studies where common times of measurement are planned, but missing data are accommodated in that one or more measurement sequences may be incomplete.

Anthropometry↗
PubMed1994

PC program for assessing the relationship between rate of change and initial value.

A menu-driven PC program implementing Blomqvist's [J. Am. Stat. Assn. 72, 746-749, 1977] method for assessing the relationship between rate of change and initial value is described, illustrated and made available. It is shown that the naive approach to this problem--computing the correlation between the initial value and either the amount or rate of change--results in a negatively biased estimator. The extent of this bias can be dramatic and may lead investigators to conclude that a negative correlation is present when none exists; or that there is no correlation when in fact the correlation is positive. Blomqvist's (maximum likelihood) estimator avoids this bias, and is obtained by a transformation of the naive estimator.

Algorithms↗
PubMed1994

A PC program for computing confidence bands for average and individual growth curves.

Dawson et al. (Am. J. Med. Genet. 7, 529-536, 1980) developed a procedure for constructing confidence bands for both average and individual growth curves which may be of considerable value in the study of growth and development. This paper describes their method for constructing, and provides a menu-driven GAUSS386i program for computing these confidence bands. It is demonstrated how these bands are useful for both the diagnosis and prognostication of growth patterns with known levels of confidence. It is assumed that the study is planned so that individuals will be measured at the same times, but missing data are allowed.

Confidence Intervals↗
PubMed1994

PC program for growth prediction in the two-stage polynomial growth curve model.

We consider the problem of growth prediction in the context of the two-stage (or random coefficients) one-sample polynomial growth curve model and provide a PC program, written in GAUSS386i, to perform the associated computations. The problem considered is that of estimating the value of the measurement under consideration for a 'new' individual at the Tth time point given measurements on that individual at T-1 previous points in time and the values of the measurement on N 'similar' individuals at all T time points. The times of measurement t1, t2, ..., tT need not be equally spaced, but we assume that each of the N individuals comprising the normative sample were measured at these times. The method and the program are illustrated using the data set previously considered (Schneiderman and Kowalski, Am J Phys Anthrop, 67 (1985) 323-333) consisting of mandibular ramus height measurements (in mm) for 12 male rhesus monkeys at T = 5 yearly intervals (coded 1, 2, 3, 4, and 5). Results are compared with those obtained under a less restrictive set of assumptions concerning the covariance matrix of the observations than is made in the context of the two-stage model. It is seen that the accuracies of prediction of the two methods, for this and other data sets, are quite close, suggesting that the less restrictive model may be preferred in many situations.

Animals↗
PubMed1994

Implementation of exact and approximate randomization tests for polynomial growth curves.

Two stand-alone, menu-driven PC programs, written in GAUSS386i, which compare groups of growth curves in a completely randomized design using either (a) exact or (b) approximate randomization tests, are described, illustrated, and made available to interested readers. The programs accommodate missing data in the context of studies planned to have common times of measurement, but where some of the measurement sequences are incomplete. The measurement whose growth is being monitored need not have a Gaussian distribution. We consider the hypothesis that the mean growth curves in G groups are the same; and either compute the exact P value (exact test), or estimate, and provide a confidence interval for, the P value (approximate test).

Algorithms↗
PubMed1994

GTRACK: a PC program for computing Goldstein's growth constancy index and an alternative measure of tracking.

This paper reviews Goldstein's 'growth constancy index,' Xi, a measure of tracking which can be used to determine whether or not individuals maintain their relative positions in the distribution of a given measurement as that distribution changes over time. We suggest that Xi is an appropriate measure of tracking when the (standardized) measurements arise in the context of a Model I ANOVA, but that the intraclass correlation coefficient, rI, may be preferred when a Model II ANOVA is applicable. We also describe--and make available--a PC program which allows the user to choose between Model I and Model II, and computes the appropriate tracking index and confidence intervals for the corresponding parameter.

Algorithms↗
PubMed1994

PC program for assessing the effect of a treatment when subjects are growing: the randomized parallel groups design.

A method for separating the effects of a treatment from those of normal development in the case of a randomized parallel groups design with pre- and post-treatment measures is described and implemented. The program allows the user to enter either summary statistics (published data are often in this form), or the pre- and post-treatment measurements for each individual. The program is illustrated using data reflecting the extent to which a treatment can be expected to impede normal growth, but the method and program are more general than this. All that is required is that the measurement be one that normally increases over time.

Analysis of Variance↗
PubMed1994

Extension of the Carter-Yang polynomial growth curve model to allow unique times of measurement for subjects.

A PC program extending the procedure due to Carter and Yang (Commun Stat: Theory Methods, 8 (1986) 2507-2526) to allow unique times of measurement for subjects is described, illustrated and made available. Given longitudinal observations on each of N subjects comprising a single group, this program determines the lowest degree polynomial in time adequate to fit the average growth curve (AGC); estimates this curve and provides confidence bands for the AGC, and confidence intervals for the corresponding polynomial regression coefficients; and so-called prediction intervals which, with a given level of confidence, will contain the growth curve of a 'new' subject from the same population of which the N subjects constitute a random sample. Two kinds of missing data are accommodated. First, in the context of studies planned so that subjects will be measured at identical times and, second, in unstructured studies where subjects may present with their own, unique times of measurement.

Body Height↗
PubMed1994

Assessing the effect of a treatment when subjects are growing at different rates.

The analysis of covariance is often used in the context of premeasure/postmeasure designs to compare treatment and control groups in both randomized [1] and nonrandomized [2] studies. The intent is to adjust the difference between the changes in the 2 groups for any difference which might exist at baseline, i.e., for any difference between the premeasures in the 2 groups. An important assumption underlying the use of the analysis of covariance is that the slopes of the lines for the regression of the postmeasure on the premeasure in the 2 groups are equal. In this paper we describe a program which can be used to test the hypothesis of equal slopes; and performs an alternative analysis which does not depend on this assumption. This is done in the context of comparing treatment and control groups with respect to a measurement subject to natural maturation as in [3]. Equal slopes in this context means equal growth rates; unequal slopes implies that the 2 groups are growing at different rates. The method, known as the Johnson-Neyman procedure [4] is, however, more general than this, and can be used in any two-sample comparison where an alternative to the usual analysis of covariance is deemed appropriate. The procedure identifies a 'region of significance' which is especially useful in practice. This region consists of a set of values of the premeasure for which the treatment and the control groups are significantly different with respect to the postmeasure.

Analysis of Variance↗
PubMed1994

Biomechanical properties of small bone screws.

PURPOSE: To evaluate systematically the biomechanical properties of 13 popular screw designs, ranging from 0.8 to 2.0 mm in diameter. METHODS: Screws were characterized in terms of external, core, and drill diameter; cutting flute and head design; material; pitch, thread depth; and height of shank (unthreaded portion) and shank with plate. They were tested in standardized bone specimens (2 x 2.5cm slabs of fresh bovine femur) 1, 2, 3, and 4-mm thick. For each screw-bone thickness combination, 10 trials were conducted to determine push-out force (POF) and another 10 trials to determine insertion (IT) and maximum torque (MT) yielding a total of 1,040 tests. RESULTS: Among the 13 different screws, in 1-mm thick bone, both the lowest (108.5 N) and highest (294.9 N) POF were created by 2-mm screws (P < .001); that with the lowest POF had a long unthreaded shank and pitch, that with highest POF had a short unthreaded shank and pitch. Screws with 0.8- to 1.5-mm diameters showed no differences in POF. The 2-mm screw with the lowest POF also had the lowest MT in 1-mm thick bone compared with the other 2-mm screws (P < .001). In thicker bones (> 2 mm), two 2-mm screws showed 30% to 50% lower MT than the other same size screws (P < .001) because their head slots stripped easily. When all screws were considered together for a particular bone thickness, torque was strongly predicted by screw diameter (MT: r = .94, P < .001; IT: r = 0.92, P < .001). Screws with the same diameters varied significantly in IT because of differences in self-tapping cutting flute design. CONCLUSION: External diameter, unthreaded shank height, head slot, and self-tapping cutting flute design had the greatest impact on screw strength and efficiency in thin cortical bone. Thread depth, core diameter, and metal type did not affect performance significantly. Under these highly standardized in vitro conditions, the ideal 2-mm screw has an unthreaded shank that is as short as possible, and the pitch is about 0.8 mm. Additional aspects of a clinical situation beside holding strength must, however, be considered when choosing a screw.

Analysis of Variance↗
PubMed1994

Analysis of longitudinal data in craniofacial research: some strategies.

Although it is generally acknowledged that longitudinal data provide the most information on growth and development and other time-dependent phenomena, such data are often analyzed by conventional (cross-sectional) statistical methods. This widespread practice ignores the distinctive characteristics (e.g., covariance structure) of longitudinal data and may yield misleading results. The purpose of this article is to present some strategies and make available computer programs for the appropriate analysis of longitudinal data. User-friendly PC programs for the estimation of average growth curves, computation of tracking indices, prediction of future values, diagnosis, classification, clustering, estimation of missing values, and testing hypotheses concerning individual and group differences are presented. Benefits of these methods over the usual techniques are illustrated with the example of maxillary growth in the rhesus monkey.

Animals↗