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Biomedical subjects

S M Willis

Publications and source records attributed to S M Willis.

At least 37 records · Page 2Linked to original sources
PubMed1993

Longer-term growth prediction using GAUSS.

In several areas of biomedicine, one needs to predict future measurements for a growing individual on the basis of longitudinal data. Here we consider the problem of estimating the values of a given measurement for a particular individual at T-T* points in time, given T* observations on that individual, and all T values for a sample of N "similar" individuals. This extends our previous discussion [Schneiderman et al., Comput. Biol. Med. 22, 181-188 (1992)], which was limited to the case T* = T-1, to longer-term predictions. We again make a user-friendly GAUSS program available to perform the associated computations. Examples illustrating the use of the program and the accuracy of the predictions it provides are included.

Algorithms↗
PubMed1993

A GAUSS program for computing the Foulkes-Davis tracking index for polynomial growth curves.

We have previously published a GAUSS program for computing the Foulkes-Davis tracking index, gamma, from a one-sample longitudinal data set when no assumptions were made concerning the structure of the individual growth curves (Schneiderman et al., Am J Hum Biol, 4 (1992) 417-420). In this paper we consider the computation of the Foulkes-Davis index assuming that each individual growth curve may be adequately represented by a polynomial function in time and a GAUSS program performing these computations is made available. As with the two other tracking indices we have described, gamma and kappa (Schneiderman et al., Am J Hum Biol, 2 (1990) 475-490), this one can be used to evaluate regularity in patterns of growth or adaptation. An example is presented where statural growth in the same three groups considered in the earlier papers are analyzed. The small disparities between these and the earlier results are discussed in view of the different assumptions of the models and the differences in how they operationalize the concept of tracking.

Adolescent↗
PubMed1993

PC program for estimating polynomial growth, velocity and acceleration curves when subjects may have missing data.

A stand-alone, menu-driven PC program, written in GAUSS386i, for estimating polynomial growth, velocity, and acceleration curves from longitudinal data is described, illustrated and made available to interested readers. Missing data are accommodated: we assume that the study is planned so that individuals will have common times of measurement, but allow some of the sequences to be incomplete. The degrees, Di, adequate to fit the growth profiles of the N individuals are determined and the corresponding polynomial regression coefficients are calculated and can be saved in ASCII files which may then be imported into a statistical computing package for further analysis. Examples of the use of the program are provided.

Achondroplasia↗
PubMed1993

PC program extending the two-stage polynomial growth curve model to allow missing data.

A stand-alone, menu-driven PC program, written in GAUSS386i, extending the analysis of one-sample longitudinal data sets satisfying the two-stage polynomial growth curve model (Ten Have et al., Am J Hum Biol, 3 (1991) 269-279) to allow missing data is described, illustrated and made available to interested readers. The method and the program are illustrated using data previously analyzed by the authors (Schneiderman and Kowalski, Am J Phys Anthropol, 67 (1985) 323-333) but with several randomly chosen data points discarded and treated as missing.

Animals↗
PubMed1993

Regression imputation of missing values in longitudinal data sets.

A stand-alone, menu-driven PC program, written in GAUSS, which can be used to estimate missing observations in longitudinal data sets is described and male available to interested readers. The program is limited to the situation in which we have complete data on N cases at each of the planned times of measurement t1, t2,..., tT; and we wish to use this information, together with the non-missing values for n additional cases, to estimate the missing values for those cases. The augmented data matrix may be saved in an ASCII file and subsequently imported into programs requiring complete data. The use of the program is illustrated. Ten percent of the observations in a data set consisting of mandibular ramus height measurements for N = 12 young male rhesus monkeys measured at T = 5 time points are randomly discarded. The augmented data matrix is used to determine the lowest degree polynomial adequate to fit the average growth curve (AGC); the regression coefficients are estimated and confidence intervals for them are determined; and confidence bands for the AGC are constructed. The results are compared with those obtained when the original complete data set is used.

Animals↗
PubMed1993

A PC program to aid in the choice of the design matrix in multiple linear regression.

A PC program, DESIGN, which can be used to evaluate and compare alternative choices of the design matrix, X, in the general linear model y = X beta + epsilon is described, illustrated and made available to interested readers. Given X, the program (1) computes various measures of the 'stability' of X and X'X and (2) determines the precisions of estimates of the model parameters, beta, and of predicted values, ŷ, at the given design points. Examples focusing on polynomial regression are given.

Data Interpretation, Statistical↗
PubMed1992

A PC program for growth prediction in the context of Rao's polynomial growth curve model.

We consider the problem of growth prediction in the context of Rao's [1] one-sample polynomial growth curve model and provide a PC program, written in GAUSS, to perform the associated computations. Specifically, 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 leave-one-out method on a sample of N = 12 male rhesus monkeys whose mandibular ramus height was measured five times at yearly intervals.

Animals↗
PubMed1992

A PC program for performing multigroup longitudinal comparisons using the Potthoff-Roy analysis and orthogonal polynomials.

A PC-program performing the Potthoff-Roy (PR) multigroup (G-sample) analysis of longtidinal data is described and illustrated. This program and the underlying statistical model are useful in the comparison of several longitudinal samples. Applications include the study of growth, development, adaptation, aging, and treatment effects (in short, any phenomenon in which the passage of time is important) for which serial data are available. Specifically, this method fits polynomials to the average growth curves in the samples, and tests hypotheses concerning the curves themselves and the individual coefficients of the polynomials. The program features the utilization of orthogonal polynomial regression coefficients (OPRCs) and is written in GAUSS, a relatively inexpensive yet comprehensive matrix programming language. It is documented that using OPRCs to comprise the within-individual or time design matrix has several advantages over the more usual choice of the successive-powers-of-t form of this matrix and an example of one important such advantage is provided. GAUSS was employed to make the program readily-accessible (i.e., executable code) to biomedical investigators. The GAUSS compiler is not required to run this program. Information regarding the availability of the program is provided in the Appendix.

Child↗
PubMed1991

Rao's polynomial growth curve model for unequal-time intervals: a menu-driven GAUSS program.

For lack of alternatives, longitudinal data are often analyzed with cross-sectional statistical methods, for instance, t-tests, ANOVA and ordinary least-squares regression. Appropriate statistical software has been generally unavailable to investigators using serial records to study growth and development or treatment effects. In an earlier paper (Schneiderman and Kowalski, Am. J. Phys. Anthropol., 67 (1985) 323-333.) we described a suitable method, Rao's polynomial growth curve model (Rao, Biometrika, 46 (1959) 49-58), and provided an SAS computer program for the analysis of a single sample of complete longitudinal data. This method included the computation of an average polynomial growth curve, its 95% confidence band, its coefficients and corresponding confidence intervals. The present paper extends this method to accommodate a sample with observations made at unequal time-intervals. Significant improvements in the accessibility, operation and user-friendliness of the program have been made, facilitated by recent advances in microcomputer technology. This stand-alone GAUSS program (no compiler necessary) runs on PC-compatibles and is available at a nominal cost. In this report we provide an overview of the statistical model, the general structure of the program, and give an example in which a developmental variable (human upper incisor angulation) is analyzed. Ease of installation and use, speed of execution and color graphic displays of growth curves and confidence bands, and most importantly, suitability to longitudinal data, make this method/program a potentially valuable tool for those interested in growth, development, and treatment effects in humans and other species. Some areas in which this method will have immediate applications are orthodontics, maxillofacial surgery and pediatrics.

Adolescent↗
PubMed1989

Pancreatic duct-portal vein fistula.

We describe a case of pancreatic duct-portal vein fistula discovered by endoscopic retrograde cholangiopancreatography, with confirmatory computed tomography and angiographic studies. The fistula was associated with chronic pancreatitis that was complicated by recurrent gram-negative bacteremia and peripheral subcutaneous fat necrosis, although pancreatic pseudocyst was not present. Even though surgical treatment was recommended, medical complications precluded surgery and the patient recovered with supportive therapy only. Follow-up endoscopic retrograde cholangiopancreatography showed spontaneous closure of the fistulous connection.

Cholangiopancreatography, Endoscopic Retrograde↗
PubMed1985

Cytophagic histiocytic panniculitis. Systemic histiocytosis presenting as chronic, nonhealing, ulcerative skin lesions.

Systemic histiocytosis was found in a patient who presented with chronic, nodular, and ulcerative skin lesions. The patient's hospital course was complicated by persistent fever, thrombocytopenia, severe neutropenia, and coagulation abnormalities. Treatment consisted only of splenectomy and supportive care. Postoperatively, the patient's skin lesions and the fever, pancytopenia, and coagulopathy resolved. Marked proliferation of histologically benign macrophages was observed in dermal, splenic, hepatic, and lymphoid tissues; leukophagocytosis and erythrophagocytosis were clearly demonstrated. This illness is most consistent with cytophagic histiocytic panniculitis, a newly described syndrome.

Adipose Tissue↗
PubMed1984

Streptokinase-induced subcapsular hematoma of the liver.

Complications with thrombolytic therapy have been shown to occur no more frequently than with conventional anticoagulant therapy. Hemorrhagic complications and allergic skin reactions are the most frequently encountered adverse effects. The vast majority of the associated bleeding complications have been related to invasive procedure and monitoring techniques. The administration of systemic streptokinase was complicated in one case by development of progressive abdominal pain and hypotension necessitating an emergency exploratory laparotomy. A ruptured subcapsular hematoma of the left lobe of the liver was found and successfully repaired. This case of visceral hemorrhage complicating streptokinase therapy was not related to previous abdominal trauma or invasive procedure.

Aged↗
PubMedDate not supplied

PC program implementing an alternative to the paired t-test which adjusts for regression to the mean.

In many biomedical research contexts, treatment effects are estimated from studies based on subjects who have been recruited because of high (low) measurements of a response variable, e.g., high blood pressure or low scores on a stress test. In this situation, simple change scores will overestimate the treatment effect; and the use of the paired t-test may find significant change due not to the treatment per se but, rather, due to regression towards the mean. A PC program implementing a procedure for adjusting the observed change for the regression effect in simple pre-test-post-test experiments is described, illustrated, and made available to interested readers. The method is due to Mee and Chua (Am Stat, 45 (1991) 39-42) and may be considered as an alternative to the paired t-test which separates the effect of the treatment from the so-called regression effect.

Adolescent↗
PubMedDate not supplied

ANCOVA for nonparallel slopes: the Johnson-Neyman technique.

The Johnson-Neyman (JN) procedure, as originally formulated (Stat Res Mem, 1 (1936) 57-93), applies to a situation in which measurements on 1 dependent (response) variable, X, and 2 independent (predictor) variables, Z1 and Z2, are available for the members of 2 groups. The expected value of X is assumed to be a linear function of Z1 and Z2, but not necessarily the same function for both groups. The JN technique is used to obtain a set of values for the Z variables for which one would reject, at a specified level of significance alpha (e.g., alpha = 0.05), the hypothesis that the 2 groups have the same expected X values. This set of values, or 'region of significance,' may then be plotted to obtain a convenient description of those values of Z1 and Z2 for which the 2 groups differ. The technique can thus be described as a generalization of the analysis of covariance (ANCOVA) which does not make the assumption that the regression coefficients for the regression of X on the covariates, Z1 and Z2, are equal in the groups being compared. In this paper we describe, illustrate and make available a menu-driven PC program (TXJN2) implementing the JN procedure.

Analysis of Variance↗