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Biomedical subjects

C R Mehta

Publications and source records attributed to C R Mehta.

At least 19 recordsLinked to original sources
PubMed2000

Ride vibration on tractor-implement system.

India is the largest manufacturer of tractors in the world. They are used for primary and secondary tillage operations and as a means of transportation. Vibration in tractor driving can cause deafness and disorders of the spinal column and stomach. The effect of implements on tractor ride is not well understood in India. The present study was undertaken to quantify ride vibration of a low horsepower tractor-implement system. Tractor ride vibration levels have been measured at the person-seat interface along three mutually perpendicular axes, longitudinal, lateral and vertical, under different operating conditions. It was observed that the acceleration levels increased as forward speed of travel increased under most of the operating conditions. There was no conclusive difference in measured acceleration levels on a tar-macadam road and a farm road during transport mode. The measured ride vibration levels under different operating conditions were evaluated as per ISO 2631/1 (1985), Geneva, and BS 6841 (1987), London, standards. On the basis of this study, it is concluded that the exposure time for the tractor operator should not exceed 2.5 h during ploughing and harrowing operations. Increasing exposure time may cause severe discomfort, pain and injury.

Agriculture↗
PubMed1996

Efficiency robust tests of independence in contingency tables with ordered classifications.

Ordered categorical data occur frequently in biomedical research. The linear by linear association test for ordered R x C tables permits the investigator to specify row and column scores for analysis. When an investigator believes that there may be more than one set of reasonable scores or when more than one investigator proposes scores, we need a method to decide upon a single procedure to use. We show how to use efficiency robustness principles to combine tests from two or more sets of scores into one robust test for analysis. This test minimizes the worst possible efficiency loss over all the sets of scores. We illustrate the methodology for the R x C case and, in detail, for the important special 2 x C case.

Alcohol Drinking↗
PubMed1995

Exact logistic regression: theory and examples.

We provide an alternative to the maximum likelihood method for making inferences about the parameters of the logistic regression model. The method is based appropriate permutational distributions of sufficient statistics. It is useful for analysing small or unbalanced binary data with covariates. It also applies to small-sample clustered binary data. We illustrate the method by analysing several biomedical data sets.

Algorithms↗
PubMed1994

The exact analysis of contingency tables in medical research.

A unified view of exact nonparametric inference, with special emphasis on data in the form of contingency tables, is presented. While the concept of exact tests has been in existence since the early work of RA Fisher, the computational complexity involved in actually executing such tests precluded their use until fairly recently. Modern algorithmic advances, combined with the easy availability of inexpensive computing power, has renewed interest in exact methods of inference, especially because they remain valid in the face of small, sparse, imbalanced, or heavily tied data. After defining exact p-values in terms of the permutation principle, we reference algorithms for computing them. Several data sets are then analysed by both exact and asymptotic methods. We end with a discussion of the available software.

Accident Prevention↗
PubMed1994

Exact permutational tests for group sequential clinical trials.

An efficient numerical algorithm is developed for computing stopping boundaries for group sequential clinical trials. Patients arrive in sequence, and are randomized to one of two treatments. The data are monitored at interim time points, with a fresh block of patients entering the study from one monitoring point to the next. The stopping boundaries are derived from the exact joint permutational distribution of the linear rank statistics observed across all the monitoring times. Specifically, the algorithm yields the exact boundary generating function, Pr(W1 < b1, W2 < b2, ..., Wi-1 < bi-1, Wi = wi), where Wj is the linear rank statistic at the jth interim time point. The distribution theory is based on assigning ranks after pooling all the patients who have entered the study, and then permuting the patients to the two treatments independently within each block of newly arrived patients. The methods are applicable for an arbitrary number of monitoring times, which need not be specified at the start of the study. The data may be continuous or categorical, and censored or uncensored. The randomization rule for treatment allocation can be adaptive. The algorithm is especially useful during the early stages of a clinical trial, when very little data have been gathered, and stopping boundaries are based on the extreme tails of the relevant boundary generating function. In that case the corresponding large-sample theory is not very reliable. To illustrate the techniques we present a group sequential analysis of a recently completed study by the Eastern Cooperative Oncology Group.

Algorithms↗
PubMed1993

Power and sample size calculations for exact conditional tests with ordered categorical data.

We develop an algorithm for computing sample sizes, equal or unequal, for categorical data. We illustrate its use in the two-sample setting using the Wilcoxon rank-sum statistic, but the algorithm accommodates the entire class of linear rank statistics and can be extended to include nonlinear rank statistics as well. The sample size determinations can be based on either exact power or on a very precise Monte Carlo estimate of it. To reduce the computations further, power can be computed as a function of asymptotic critical values when the number of categories is not too small. For the Wilcoxon statistic we show that this approximation works well if there are more than five response categories.

Humans↗
PubMed1988

Exact inference for matched case-control studies.

In an epidemiological study with a small sample size or a sparse data structure, the use of an asymptotic method of analysis may not be appropriate. In this paper we present an alternative method of analyzing data for case-control studies with a matched design that does not rely on large-sample assumptions. A recursive algorithm to compute the exact distribution of the conditional sufficient statistics of the parameters of the logistic model for such a design is given. This distribution can be used to perform exact inference on model parameters, the methodology of which is outlined. To illustrate the exact method, and compare it with the conventional asymptotic method, analyses of data from two case-control studies are also presented.

Algorithms↗
PubMed1986

Anxiety levels in patients randomized to adjuvant therapy versus observation for early breast cancer.

We studied anxiety levels in 68 patients who had been randomized to adjuvant chemotherapy v observation on two Eastern Cooperative Oncology Group (ECOG) protocols. All subjects were women who had undergone total or modified radical mastectomy for breast cancer. Immediately before breast protocol randomization and again 3, 6, and 12 months later, patients completed two self-report measures: the State-Trait Anxiety Inventory and the SCL-90. There were no consistent trends in anxiety levels over time. At each test point, patients under observation displayed higher anxiety scores than did patients receiving adjuvant therapy, but these differences failed to attain statistical significance. Power calculations indicate that these results rule out the possibility of major differences in anxiety levels among patients randomized to observation v adjuvant therapy, but a larger patient sample is required before a definitive statement can be made about smaller differences.

Aged↗
PubMed1986

An intervention study of tobacco chewing and smoking habits for primary prevention of oral cancer among 12,212 Indian villagers.

In a house-to-house screening survey, 12,212 tobacco chewers and smokers were selected from the rural population in the Ernakulam district, Kerala state, India. These individuals were interviewed for their tobacco habits and examined for the presence of oral cancer and precancerous lesions, first in a baseline survey, and then annually, over a five-year period. They were educated using personal and mass media communication to give up their tobacco habits. The control group was provided from the results of the first five years of a 10-year follow-up study conducted earlier by the authors in the same area with the same methodology but on different individuals without any educational intervention. The stoppage of the tobacco habit was substantially higher in the intervention group (9.4%) compared to the control group (3.2%). A logistic regression analysis showed that the behavioural intervention was helpful to all categories of individuals, however, the effect was different for different categories: intervention was more helpful to men, chewers, and those with a long duration of the habit. These individuals rarely quit their habit without intervention.

Adolescent↗
PubMed1984

Charts for the early stopping of pilot studies.

Cooperative oncology groups usually run pilot studies of new agents or combinations concurrently with their major randomized clinical trials. A primary objective of these studies is to determine whether the new regimen should be tested further in a group-wide clinical trial. The accrual goals of such pilot studies are typically fixed in advance at between 30 and 40 patients, on the grounds that this number provides a reasonably tight confidence interval on the true response rate. Nevertheless early termination of pilot studies is often desirable either because the regimen appears inactive or because early results indicate extreme activity and justify immediate testing in a randomized study. Statistical charts are provided for early termination in both these situations. The charts are read by specifying the number of evaluable patients already accrued, the number of responses observed and the minimum true response rate, theta 0, at which the regimen would be considered active. The charts provide the posterior probability that the true response rate exceeds theta 0, that is, that the regimen is active. An additional chart that computes a 90% probability interval for the true response rate, based on the observed rate and sample size, is also provided. The use of the chart is illustrated with two examples from the Eastern Cooperative Oncology Group.

Antineoplastic Agents↗
PubMed1984

Exact confidence intervals following a group sequential test.

A numerical method is used to compute confidence intervals, which have exact coverage probabilities, for the mean of a normal distribution following a group sequential test. This method, which uses an ordering of the sample space similar to that employed by Siegmund (1978, Biometrika 65, 341-349), is contrasted with the usual confidence interval for the mean.

Biometry↗
PubMed1984

Exact significance testing to establish treatment equivalence with ordered categorical data.

This communication concerns the problem of establishing the therapeutic equivalence of two treatments that are being compared on the basis of ordered categorical data. The problem is formulated as a significance test in which the null hypothesis specifies a treatment difference. An efficient numerical algorithm for computing the exact significance level is provided, along with a simple method for obtaining the asymptotic significance level. Both methods are applied to a clinical trial of a new agent versus an active control. Guidelines for when to use the exact procedure and when to rely on asymptotic theory are provided.

Biometry↗
PubMed1980

Chemotherapy of extensive large cell and adenocarcinoma of the lung: a randomized trial in 210 patients.

Two hundred ten patients with advanced adenocarcinoma of the lung were entered into a two-arm randomized trail. Cytoxan + CCNU + methotrexate was compared to Adriamycin and procarbazine. The tumor response to CCM was significantly higher than the tumor response to Adriamycin and procarbazine. No significant difference existed between the two treatments with respect to survival. Initial performance status, weight loss prior to therapy, and response to therapy were all found to be significant prognostic factors. Median survival time relative to responders in both treatment groups was 31.7 weeks and 15.8 weeks for non-responders.

Adenocarcinoma↗
PubMed1979

MACC chemotherapy for adenocarcinoma and epidermoid carcinoma of the lung: low response rate in a Cooperative Group Study. Eastern Cooperative Oncology Group.

The MACC (methotrexate, adriamycin, cyclophosphamide, CCNU) regimen was administered to 43 patients with advanced epidermoid and adenocarcinoma of the lung. Only 5 patients (12%), all of whom were ambulatory responded with partial remissions. Median time to progression for the 5 responders was 20 weeks from start of treatment. Median survival was 15.5 weeks for patients with epidermoid cancer and 14.4 weeks for those with adenocarcinoma. Hematologic toxicity was severe, with 2 treatment-related deaths during profound myelosuppression. White blood counts below 2000/microliter were reported in 47%, and below 1,000/microliter in 26%. Since the activity of this regimen, given as it was in full doses, is not superior to that achieved with standard doses of single agents which are less toxic, further employment of the MACC regimen is not recommended, either for advanced disease or as a surgical adjuvant.

Adenocarcinoma↗