Circular Systematic Sampling Research Articles

Risk factors for maternal mortality in Delhi slums: A community-based case-control study

In order to develop, implement and evaluate policy for reducing maternal mortality, it is essential to study the risk factors associated with maternal deaths. The study aims to determine the epidemiological risk factors and its related causes associated with maternal deaths in Delhi slums. A community-based case-control study was designed, wherein snowball-sampling method was used to identify the maternal deaths (cases) in the community and circular systematic random sampling procedure was used to select the controls from the same area where a maternal death was found. Data on 70 cases and 384 controls that had live births as the outcome of the pregnancy were analyzed. Logistic regression was applied to identify the risk factors. In the study population, most of the deliveries were conducted at home by untrained 'dais.' Cases were mostly illiterate, young, having high parity and no antenatal care taken during pregnancy (P CONCLUSIONS: The study findings suggest that women should be educated about the importance of antenatal registration and regular checkups. Untrained 'dais' should be trained to recognize the obstetric complications at an early stage and refer high-risk cases for adequate management. These preventive measures could help in reducing maternal mortality at the community level.

On error prediction in circular systematic sampling

An extended covariogram model is discussed for estimating the precision of circular systematic sampling. The extension is motivated by recent developments in shape analysis of featureless planar objects. Preliminary simulation results indicate that it is important to consider the extended covariogram model.

Modified balanced circular systematic sampling

New modifications of balanced circular systematic sampling and centered circular systematic sampling procedures are introduced here. We study the efficiency of the suggested sampling designs for several populations and find that our procedures are suitable to estimate the means of populations which show approximately linear and parabolic trends.

Additional Circular Systematic Sampling Methods

Several systematic sampling methods have been used to estimate the population mean when size of the population is a multiple of sample size. Among these, only few methods have been extended and used to estimate mean of the population when its size is not a multiple of sample size. In this paper, new methods called balanced circular systematic sampling and centered circular systematic sampling are introduced by extending balanced systematic sampling method and centered systematic sampling method respectively. These methods are compared with circular systematic sampling using average variance of corrected sample means for populations exhibiting approximate linear and parabolic trends. The suggested methods are found suitable to estimate the population mean.

Circular Systematic Sampling with Varying Probabilities

Certain conditions connecting the population size, sample size and the sampling interval in circular systematic sampling with equal probabilities are known. We present here a simple “condition” connecting the sample size, size-measures and the sampling interval in pps circular systematic sampling. The condition is important in noting limitations on sample-sizes when a sampling interval is pre-assigned.