SEQUENTIAL DATA WEIGHTING PROCEDURES FOR COMBINED RATIO ESTIMATORS IN COMPLEX SAMPLE SURVEYS

In sample surveys weighting is applied to data to increase the quality of estimates. Data weighting can be used for several purposes. Sample design weights can be used to adjust the differences in selection probabilities for non-self weighting sample designs. Sample design weights, adjusted for nonresponse and non-coverage through the sequential data weighting process. The unequal selection probability designs represented the complex sampling designs. Among many reasons of weighting, the most important reasons are weighting for unequal probability of selection, compensation for nonresponse, and post-stratification. Many highly efficient estimation methods in survey sampling require strong information about auxiliary variables, x. The most common estimation methods using auxiliary information in estimation stage are regression and ratio estimator. This paper proposes a sequential data weighting procedure for the estimators of combined ratio mean in complex sample surveys and general variance estimation for the population ratio mean. To illustrate the utility of the proposed estimator, Turkish Demographic and Health Survey 2003 real life data is used. It is shown that the use of auxiliary information on weights can considerably improve the efficiency of the estimates

Diquark condensation effects on hot quark star configurations

The equation of state for quark matter is derived for a nonlocal, chiral quark model within the mean field approximation.We investigate the effects of a variation of the formfactors of the interaction on the phase diagram of quark matter. Special emphasis is on the occurrence of a diquark condensate which signals a phase transition to color superconductivity and its effects on the equation of state under the condition of beta- equilibrium and charge neutrality. We calculate the quark star configurations by solving the Tolman- Oppenheimer- Volkoff equations and obtain for the transition from a hot, normal quark matter core of a protoneutron star to a cool diquark condensed one a release of binding energy of the order of Delta M c^2 ~ 10^{53} erg. We find that this energy could not serve as an engine for explosive phenomena since the phase transition is not first order. Contrary to naive expectations the mass defect increases when for a given temperature we neglect the possibility of diquark condensation.Comment: 24 pages, 2 tables, 8 figures, references added, figures and text improve

The phase diagram of three-flavor quark matter under compact star constraints

The phase diagram of three-flavor quark matter under compact star constraints is investigated within a Nambu--Jona-Lasinio model. Local color and electric charge neutrality is imposed for beta-equilibrated superconducting quark matter. The constituent quark masses and the diquark condensates are determined selfconsistently in the plane of temperature and quark chemical potential. Both strong and intermediate diquark coupling strengths are considered. We show that in both cases, gapless superconducting phases do not occur at temperatures relevant for compact star evolution, i.e., below T ~ 50 MeV. The stability and stucture of isothermal quark star configurations are evaluated. For intermediate coupling, quark stars are composed of a mixed phase of normal (NQ) and two-flavor superconducting (2SC) quark matter up to a maximum mass of 1.21 M_sun. At higher central densities, a phase transition to the three-flavor color flavor locked (CFL) phase occurs and the configurations become unstable. For the strong diquark coupling we find stable stars in the 2SC phase, with masses up to 1.326 M_sun. A second family of more compact configurations (twins) with a CFL quark matter core and a 2SC shell is also found to be stable. The twins have masses in the range 1.301 ... 1.326 M_sun. We consider also hot isothermal configurations at temperature T=40 MeV. When the hot maximum mass configuration cools down, due to emission of photons and neutrinos, a mass defect of 0.1 M_sun occurs and two final state configurations are possible.Comment: 12 pages, 11 figure

Sequential data weighting procedures for combined ratio estimators ın complex sample surveys

In sample surveys weighting is applied to data to increase the quality of estimates. Data weighting can be used for several purposes. Sample design weights can be used to adjust the differences in selection probabilities for non-self weighting sample designs. Sample design weights, adjusted for nonresponse and noncoverage through the sequential data weighting process. The unequal selection probability designs represented the complex sampling designs. Among many reasons of weighting, the most important reasons are weighting for unequal probability of selection, compensation for nonresponse, and post-stratification. Many highly efficient estimation methods in survey sampling require strong information about auxiliary variables, x. The most common estimation methods using auxiliary information in estimation stage are regression and ratio estimator. This paper proposes a sequential data weighting procedure for the estimators of combined ratio mean in complex sample surveys and general variance estimation for the population ratio mean. To illustrate the utility of the proposed estimator, Turkish Demographic and Health Survey 2003 real life data is used. It is shown that the use of auxiliary information on weights can considerably improve the efficiency of the estimates

Models for survey nonresponse and bias adjustment techniques

Survey statisticians have been dealing with the issues of nonresponse in sample surveys for many years. Due to the complex nature of the mechanism, so far it has not been easy to find a general solution to this problem. In this paper, several aspects of this topic will be elaborated on: the survey unit nonresponse bias has been examined alternatively by taking response amounts which are fixed initially and also by taking the response amounts as random variables. An overview of the components of the bias due to nonresponse will be performed. Nonresponse bias components are illustrated for each alternative approach and the amount of bias was computed for each case

Probability Sample Selection Method in Household Surveys When Current Data on Regional Population is Unavailable

Availability of the perfect sampling frame only exists in developed countries, which covers a very small proportion of the world countries. On the other hand, in developing countries lists of the latest population census counts are generally used as the sampling frame for sample surveys. Therefore, in developing countries surveys which are planned for future periods long after the census date, cannot be representative of the related time period if the same census counts are utilized. Instead, population projections and data adjustment methodologies must be used to provide a representative probability selection of the updated population. This article proposes a population projection and adjustment methodology in order to establish the ideal selection probability for household surveys. The method contains the correction on the differences of the sum of strata and aggregated values. Comparative examples are also provided to clarify the proposed methodology