Computer program for the parametric and nonparametric comparison of several groups to a control

A BASIC program is described which, upon the input of raw data from an experiment comparing several treatment groups to a control, will output group parameters (mean, SEM), test for outliers in each group (maximum normalized residual test), and examine the homogeneity of variance (Bartlett's test). Subsequently, one-way ANOVA and Dunnett's multiple comparison test are performed. The user also has the option of examining the data by nonparametric means using the Kruskal-Wallis test and a nonparametric multiple comparison test (Dunn's test). As a convenience, the program contains algorithms to generate critical table values for all the tests employed.     

PC program for obtaining orthogonal polynomial regression coefficients for use in longitudinal data analysis

Much of longitudinal data analysis begins with dimensionality reduction, i.e., the replacement of the T observations x₁, x₂, …, x_T on an individual taken at times t₁, t₂, …, t_T (not necessarily equally spaced) by a smaller number, P, of parameters which are then used to describe and compare growth processes. We focus on the class of polynomial growth curve models for one-sample data matrices in which the P regression coefficients are estimated by an equation of the form $ \hat \tau = ({\rm W'W}) $ ¹W′x and consider the choice of the design matrix W. The case in favor of using orthogonal polynomials to comprise the elements of W and provide a PC program, written in GAUSS, for obtaining them is presented. This program can be used instead of existing tables of orthogonal polynomials in the case of equally spaced time points, and to avoid laborious hand-computation to obtain them when the time points are not equally spaced. The program also computes the corresponding orthogonal polynomial regression coefficients $ \hat \alpha = (\Phi '\Phi)^{ - 1} \Phi '{\rm x} $, where Φ consists of orthogonal polynomials, which may then be input into other programs for subsequent analysis, e.g., to compare the growth profiles of several groups of individuals. Examples of the use of the program are given. Information on obtaining a copy of the program is provided in Appendix A. © 1992 Wiley-Liss, Inc.     

A cross-sectional survey comparing a free treatment program for advanced schistosomiasis japonica to a general assistance program

Parasitology Research - The prevalence and intensity of schistosomiasis has dropped dramatically in China due to an effective integrated control program. However, advanced schistosomiasis is...     

TRACK: a FORTRAN program for calculating the Foulkes-Davis tracking index

This paper describes a program that calculates the Foulkes-Davis tracking index, the probability that two individuals selected at random will have measurement curves that do not cross.     

Statistics in practice. Comparing the means of several groups

This article discusses statistical methods for comparing the means of several groups and focuses on examples from 50 Original Articles published in the Journal in 1978 and 1979. Although medical authors often present comparisons of the means of several groups, the most common method of analysis, multiple t-tests, is usually a poor choice. Which method of analysis is appropriate depends on what questions the investigators wish to ask. If the investigators want to identify which of the groups under study are different from the rest, they will need a different method from the one required if they wish simply to decide whether or not the groups share a common mean. More complicated questions about the group means call for more sophisticated techniques. Of the 50 Journal articles examined, 27 (54 per cent) used inappropriate statistical methods to analyze the differences between group means. Investigators need to become better acquainted with statistical techniques for making multiple comparisons between group means.     

A GAUSS program for computing an index of tracking from longitudinal observations

Tracking can be defined as the tendency of individuals or collections of individuals to stay within a particular course of growth over time relative to other individuals. Thus, tracking describes stability in growth patterns. This paper outlines a statistical procedure for examining tracking in a single sample of measurements made on humans or other animals. This nonparametric procedure, based on Cohen's (1960) kappa statistic, is suitable for equally or unequally spaced serial data that is complete and is appropriate for questions concerning growth as well as other time-dependent phenomena. It is a conceptually simple longitudinal method that affords insight regarding the predictability of growth within a population. For example, by tracking, one can ask if young children who are in the lowest height for age category are likely to end up in that category at an older age. A user-friendly GAUSS program is provided that generates overall as well as individual and track-specific statistics. High-resolution graphic representations of the data are also generated by the program. Examples are presented, including a tracking analysis of Guatemalan Indian children using quartiles.     

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.     

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.     

A PC based computer program to aid the preparation of solvent systems for the HPLC

An interactive computer program, SOLCOMP, is developed which calculates the volumes of the components that are to be added to obtain either a fresh solvent mixture or a new solvent system from the old one of required composition. The code is implemented in MicroSoft FORTRAN and GWBASIC which runs on any IBM compatible PC under MSDOS environment.     

Active tracking of rejected dried blood samples in a large program in Nigeria

AIM: To study the impact of rejection at different levels of health care by retrospectively reviewing records of dried blood spot samples received at the molecular laboratory for human immunodeficiency virus (HIV) early infant diagnosis (EID) between January 2008 and December 2012. METHODS: The specimen rejection rate, reasons for rejection and the impact of rejection at different levels of health care was examined. The extracted data were cleaned and checked for consistency and then de-duplicated using the unique patient and clinic identifiers. The cleaned data were ciphered and exported to SPSS version 19 (SPSS 2010 IBM Corp, New York, United States) for statistical analyses. RESULTS: Sample rejection rate of 2.4% (n = 786/32552) and repeat rate of 8.8% (n = 69/786) were established. The mean age of infants presenting for first HIV molecular test among accepted valid samples was 17.83 wk (95%CI: 17.65-18.01) vs 20.30 wk (95%CI: 16.53-24.06) for repeated samples. HIV infection rate was 9.8% vs 15.9% for accepted and repeated samples. Compared to tertiary healthcare clinics, secondary and primary clinics had two-fold and three-fold higher likelihood of sample rejection, respectively (P < 0.05). We observed a significant increase in sample rejection rate with increasing number of EID clinics (r = 0.893, P = 0.041). The major reasons for rejection were improper sample collection (26.3%), improper labeling (16.4%) and insufficient blood (14.8%). CONCLUSION: Programs should monitor pre-analytical variables and incorporate continuous quality improvement interventions to reduce errors associated with sample rejection and improve patient retention.     

Circadian rhythmicity in several small intestinal functions is independent of use of the intestine

Fifty milliliters of a liquid diet were administered daily to rats in three different ways: 1) orally, beginning at 0000 h; 2) by continuous intravenous infusion; and 3) by discontinuous intravenous infusion from 0000 to 1400 h. Animals were killed every 6 h over a 24-h period. Activity profiles as a function of time of day were determined for the following small intestinal parameters; monosaccharide transport; five disaccharidases; alkaline phosphatase; gamma-glutamyltransferase; leucylnaphthylamide hydrolyzing activity; villus height and width; and number of columnar cells lining a villus section. Circadian rhythmicity as previously reported was observed for all parameters in rats fed orally for 7 days but was not observed in any parameters in rats fed by continuous infusion for 9 days. Rats fed by discontinuous infusion for 10 days maintained circadian rhythmicity in the following functions: monosaccharide transport; disaccharidase activities; and columnar cell number. Thus, rhythmicity in these functions can exist without nutrient delivery to the alimentary tract and presumably arises from involvement of a neuro-endocrine component. The other activities tested appear to require the alimentary tract for the existence of circadian rhythmicity.     

Brief cognitive behavioral intervention in groups in a Brazilian assisted reproduction program

The study's objective was to assess the effect of a cognitive behavioral group intervention on the pregnancy rates of patients submitted to in vitro fertilization (IVF) techniques or to intracytoplasmic sperm injection (ICSI). The study was conducted on 188 patients, 93 who participated in a group of psychological intervention before the IVF and ICSI procedures and 95 patients submitted to IVF and ICSI during the same period of time, who did not participate in the intervention (control group). Clinical pregnancy was the outcome measure. Demographic and clinical variables were compared between groups in order to assess the group's homogeneity. Participants in the psychological intervention obtained a pregnancy rate of 39.8%, significantly higher than the 23.2% rate of nonparticipants (χ(2) = 6.03, p = .01, odds ratio of 22 (CI: 1.16-4.13). The data suggest that group psychological intervention before IVF and ICSI in order to control stress seems to increase the rate of success of these procedures.