Kadilar and Cingi [Ratio estimators in simple random sampling, Appl. Math. Comput. 151 (3) (2004), pp. 893-902] introduced some ratio-type estimators of finite population mean under simple random sampling. Recently, Kadilar and Cingi [New ratio estimators using correlation coefficient, Interstat 4 (2006), pp. 1-11] have suggested another form of ratio-type estimators by modifying the estimator developed by Singh and Tailor [Use of known correlation coefficient in estimating the finite population mean, Stat. Transit. 6 (2003), pp. 655-560]. Kadilar and Cingi [Improvement in estimating the population mean in simple random sampling, Appl. Math. Lett. 19 (1) (2006), pp. 75-79] have suggested yet another class of ratio-type estimators by taking a weighted average of the two known classes of estimators referenced above. In this article, we propose an alternative form of ratio-type estimators which are better than the competing ratio, regression, and other ratio-type estimators considered here. The results are also supported by the analysis of three real data sets that were considered by Kadilar and Cingi.ratio-type estimators, mean square error (MSE), transformation, efficiency,
In Gupta et al. (2010;2011), it was observed that introduction of a truth element in an optional randomized response model can improve the efficiency of the mean estimator. However, a large value of the truth parameter (T) may be needed if the underlying question is highly sensitive. This can jeopardize respondent cooperation. In what we call a "three-stage optional randomized response model," a known proportion (T) of the respondents is asked to tell the truth, another known proportion (F) of the respondents is asked to provide a scrambled response, and the remaining respondents are instructed to provide a response following the usual optional randomized response strategy where a respondent provides a truthful response (or a scrambled response) depending on whether he/she considers the question nonsensitive (or sensitive). This is done anonymously based on color-coded cards that the researcher cannot see. In this article we show that a three-stage model may turn out to be more efficient than the corresponding two-stage model, and with a smaller value of T. Greater respondent cooperation will be an added advantage of the three-stage model.
Although only three trials with 128 patients fulfilled the criteria for this systematic review, the data suggest that the use of prophylactic prosthetic mesh at the time of primary stoma formation reduces the incidence of parastomal hernia.
This article proposes two improved family of estimators for estimating the finite population mean in simple random sampling SRS and stratified random sampling S t RS . The proposed estimators always perform better than a family of ratio estimators suggested by Khoshnevisan et al. (2007) in SRS and Koyuncu and Kadilar (2009a) in S t RS. They also perform better than the ratio estimator given by Gupta and Shabbir (2008) in SRS and Koyuncu and Kadilar (2010) and Shabbir and Gupta (2011) in S t RS. The expressions for bias and mean squared error (MSE) of considered estimators are obtained. The results are illustrated by real data sets.
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