منابع مشابه
To Weight or Not to Weight: Where is the Question?
We investigate the approximability properties of several weighted problems, by comparing them with the respective unweighted problems. For an appropriate (and very general) deenition of niceness, we show that if a nice weighted problem is hard to approximate within r, then its polynomially bounded weighted version is hard to approximate within r ? o(1). Then we turn our attention to speciic pro...
متن کاملAssessing socioeconomic effects on different sized populations: to weight or not to weight?
OBJECTIVE Researchers in health care often use ecological data from population aggregates of different sizes. This paper deals with a fundamental methodological issue relating to the use of such data. This study investigates the question of whether, in doing analyses involving different areas, the estimating equations should be weighted by the populations of those areas. It is argued that the c...
متن کاملTo Weight or Not to Weight: Incorporating Sampling Effects into Model-Based Survey Analysis
The two fundamental approaches used to analyze survey data, designand model-based, differ in how they incorporate complexities of the sampling design, such as stratification, clustering and/or unequal probabilities of selection, into the survey analysis. The design-based analysis uses the sampling design as the sole source of the variability, which necessitates the use of survey sampling weight...
متن کاملAssessing socioeconomic eVects on diVerent sized populations: To weight or not to weight?
Objective—Researchers in health care often use ecological data from population aggregates of diVerent sizes. This paper deals with a fundamental methodological issue relating to the use of such data. This study investigates the question of whether, in doing analyses involving diVerent areas, the estimating equations should be weighted by the populations of those areas. It is argued that the cor...
متن کاملTo Weight or Not to Weight: Source-Normalised LDA for Speaker Recognition Using i-vectors
Source-normalised Linear Discriminant Analysis (SNLDA) was recently introduced to improve speaker recognition using i-vectors extracted from multiple speech sources. SNLDA normalises for the effect of speech source in the calculation of the between-speaker covariance matrix. Sourcenormalised-and-weighted (SNAW) LDA computes a weighted average of source-normalised covariance matrices to better e...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Value in Health
سال: 2004
ISSN: 1098-3015
DOI: 10.1016/s1098-3015(10)62173-0