An Alternative Approach to Estimation in Two-Phase Sampling Using two Auxiliary Variables

Using two-phase sampling mechanism, two alternative estimators in the presence of the available knowledge on second auxiliary variable z are considered, when the population mean of the main auxiliary variable × is unknown. The suggested estimators are found to be more eficient than the ratio-type and regression-type estimators suggested by KIREGYERA (1980, 1984).     

On the Use of Jack‐Knife Techniques in Systematic Sampling

We have proposed two general classes of ratio and product type estimators to estimate an unknown population parameter of a response variable y under systematic sampling strategy. Jack‐Knife technique is employed to make the classes almost/exactly unbiased and sampling variance of the proposed estimators are derived to the first order of approximation. The merits of the proposed estimators over other estimators are discussed in this paper.     

Monte Carlo Investigations for Relative Efficiency of Stratified Random Sampling Scheme for Estimation of Relative Risk in Case-Control Studies

Monte Carlo Investigations have been widely used in Sample Surveys in Comparing the efficiency of various methods when exact mathematical comparisons are not possible. In this paper the same has been used for comparing the efficiency of Stratified Random Sampling with respect to Simple Random Sampling for estimation of Relative Risk in Case-Control Studies. The data used relate to a Case Control study on peptic ulcer. On the basis of Monte Carlo Investigations on 50 samples of size 10–20 (Cases and Controls), it has been observed that there is considerable gain in efficiency in using Stratified Random Sampling over Simple Random Sampling. The sensitivity of the results with the change in Sample Size has also been investigated.     

Estimation of Ratio Using Rank Set Sampling

Ranked set sampling (RSS) as suggested by McIntyre (1952) and developed by Takahasi and Wakimoto (1968) is used to estimate the ratio. It is proved that by using RSS method the efficiency of the estimator relative to the simple random sampling (SRS) method has increased. Computer simulated results are given. An example using real data is presented to illustrate the computations.     

Sampling Schemes for Studying Growth of Children

Efficiency of linked cross-sectional scheme has been compared with pure longitudinal schemes for generalised estimation of norm relaxing the condition of constancy of variances. The relevant theory of estimation has been developed and the expression for the optimum estimators alongwith their variances have been derived. The percentage gain in efficiency has been calculated. It has been observed that for higher values of Q, percentage gain in efficiency of proposed scheme over cross-sectional is very high.     

Sampling strategies for using female gametophytes to estimate heterozygosity in conifers

Summary Unbiased estimators of genotype and allele frequencies and their respective variances are obtained for loci identified by mendelian segregation in haploid female gametophytes from individual trees. By a minimum sampling variance criterion, the allocation of experimental effort between the number of female gametophytes analysed per tree and the number of trees sampled per population is examined for a fixed total amount of experimental effort. For estimating heterozygosity, the optimum sampling design for many (generally most) cases is three female gametophytes per tree, but may be more than three depending upon the true genotype frequencies in the population. For estimating allele frequencies, the optimum sampling design is one female gametophyte per tree except in cases where a strong negative correlation exists between alleles within genotpyes. Guidelines are discussed for determining a suitable number of female gametophytes to be analysed per tree in order to estimate heterozygosity.     

二次等距抽样

本文提出了一种二次等距抽样方法,并提出了总体平均值的一个估计量：拼配部分的比型估计与轮换部分的样本均值的加权平均。当样本量较大时,求出了估计量的方差及最优轮换比．并对特殊情形进行了讨论和数值比较．     

Estimation of Population Regression Coefficient in Successive Sampling

An attempt has been made to derive the theory of successive sampling for estimation of regression coefficient. The situations considered are estimation of regression coefficient for current occasion, estimation of change of regression coefficients over two occasions and estimation of average of regression coefficients over two occasions. The expressions of optimum estimators along with their variances have been worked out. On comparing their efficiencies empirically, it has been observed that similar to the estimation of mean, successive sampling can also be used with advantage for estimation of regression coefficient.