17,773 research outputs found
Generalised regression estimation given imperfectly matched auxiliary data
Generalised regression estimation allows one to make use of available
auxiliary information in survey sampling. We develop three types of generalised
regression estimator when the auxiliary data cannot be matched perfectly to the
sample units, so that the standard estimator is inapplicable. The inference
remains design-based. Consistency of the proposed estimators is either given by
construction or else can be tested given the observed sample and links. Mean
square errors can be estimated. A simulation study is used to explore the
potentials of the proposed estimators
On valid descriptive inference from non-probability sample
We examine the conditions under which descriptive inference can be based
directly on the observed distribution in a non-probability sample, under both
the super-population and quasi-randomisation modelling approaches. Review of
existing estimation methods reveals that the traditional formulation of these
conditions may be inadequate due to potential issues of under-coverage or
heterogeneous mean beyond the assumed model. We formulate unifying conditions
that are applicable to both type of modelling approaches. The difficulties of
empirically validating the required conditions are discussed, as well as valid
inference approaches using supplementary probability sampling. The key message
is that probability sampling may still be necessary in some situations, in
order to ensure the validity of descriptive inference, but it can be much less
resource-demanding provided the presence of a big non-probability sample
Minimal inference from incomplete 2x2-tables
Estimates based on 2x2 tables of frequencies are widely used in statistical
applications. However, in many cases these tables are incomplete in the sense
that the data required to compute the frequencies for a subset of the cells
defining the table are unavailable. Minimal inference addresses those
situations where this incompleteness leads to target parameters for these
tables that are interval, rather than point, identifiable. In particular, we
develop the concept of corroboration as a measure of the statistical evidence
in the observed data that is not based on likelihoods. The corroboration
function identifies the parameter values that are the hardest to refute, i.e.,
those values which, under repeated sampling, remain interval identified. This
enables us to develop a general approach to inference from incomplete 2x2
tables when the additional assumptions required to support a likelihood-based
approach cannot be sustained based on the data available. This minimal
inference approach then provides a foundation for further analysis that aims at
making sharper inference supported by plausible external beliefs
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Gene duplication and an accelerated evolutionary rate in 11S globulin genes are associated with higher protein synthesis in dicots as compared to monocots
Background: Seed storage proteins are a major source of dietary protein, and the
content of such proteins determines both the quantity and quality of crop yield.
Significantly, examination of the protein content in the seeds of crop plants shows a
distinct difference between monocots and dicots. Thus, it is expected that there are
different evolutionary patterns in the genes underlying protein synthesis in the seeds
of these two groups of plants.
Results: Gene duplication, evolutionary rate and positive selection of a major gene
family of seed storage proteins (the 11S globulin genes), were compared in dicots and
monocots. The results, obtained from five species in each group, show more gene
duplications, a higher evolutionary rate and positive selections of this gene family in
dicots, which are rich in 11S globulins, but not in the monocots.
Conclusion: Our findings provide evidence to support the suggestion that gene
duplication and an accelerated evolutionary rate may be associated with higher protein
synthesis in dicots as compared to monocots
Tests for price indices in a dynamic item universe
There is generally a need to deal with quality change and new goods in the
consumer price index due to the underlying dynamic item universe. Traditionally
axiomatic tests are defined for a fixed universe. We propose five tests
explicitly formulated for a dynamic item universe, and motivate them both from
the perspectives of a cost-of-goods index and a cost-of-living index. None of
the indices satisfies all the tests at the same time, which are currently
available for making use of scanner data that comprises the whole item
universe. The set of tests provides a rigorous diagnostic for whether an index
is completely appropriate in a dynamic item universe, as well as pointing
towards the directions of possible remedies. We thus outline a large index
family that potentially can satisfy all the tests
Determinations of form factors for semileptonic decays and leptoquark constraints
By analyzing all existing measurements for ( ) decays, we find that the determinations of both the vector
form factor and scalar form factor for semileptonic
decays from these measurements are feasible. By taking the
parameterization of the one order series expansion of the and
, is determined to be , and the
shape parameters of and are
and , respectively. Combining with the average
of and lattice calculaltion, the is extracted
to be where the first error is experimental and the
second theoretical. Alternatively, the is extracted to be
by taking the as the value from the global
fit with the unitarity constraint of the CKM matrix. Moreover, using the
obtained form factors by lattice QCD, we re-analyze these
measurements in the context of new physics. Constraints on scalar leptoquarks
are obtained for different final states of semileptonic
decays
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