10,617 research outputs found
An exact adaptive test with superior design sensitivity in an observational study of treatments for ovarian cancer
A sensitivity analysis in an observational study determines the magnitude of
bias from nonrandom treatment assignment that would need to be present to alter
the qualitative conclusions of a na\"{\i}ve analysis that presumes all biases
were removed by matching or by other analytic adjustments. The power of a
sensitivity analysis and the design sensitivity anticipate the outcome of a
sensitivity analysis under an assumed model for the generation of the data. It
is known that the power of a sensitivity analysis is affected by the choice of
test statistic, and, in particular, that a statistic with good Pitman
efficiency in a randomized experiment, such as Wilcoxon's signed rank
statistic, may have low power in a sensitivity analysis and low design
sensitivity when compared to other statistics. For instance, for an additive
treatment effect and errors that are Normal or logistic or -distributed with
3 degrees of freedom, Brown's combined quantile average test has Pitman
efficiency close to that of Wilcoxon's test but has higher power in a
sensitivity analysis, while a version of Noether's test has poor Pitman
efficiency in a randomized experiment but much higher design sensitivity so it
is vastly more powerful than Wilcoxon's statistic in a sensitivity analysis if
the sample size is sufficiently large.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS508 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Error-free milestones in error prone measurements
A predictor variable or dose that is measured with substantial error may
possess an error-free milestone, such that it is known with negligible error
whether the value of the variable is to the left or right of the milestone.
Such a milestone provides a basis for estimating a linear relationship between
the true but unknown value of the error-free predictor and an outcome, because
the milestone creates a strong and valid instrumental variable. The inferences
are nonparametric and robust, and in the simplest cases, they are exact and
distribution free. We also consider multiple milestones for a single predictor
and milestones for several predictors whose partial slopes are estimated
simultaneously. Examples are drawn from the Wisconsin Longitudinal Study, in
which a BA degree acts as a milestone for sixteen years of education, and the
binary indicator of military service acts as a milestone for years of service.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS233 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Launch vehicle error sensitivity study
Booster trajectory optimization for launch vehicle range sensitivity analysi
Isolation in the construction of natural experiments
A natural experiment is a type of observational study in which treatment
assignment, though not randomized by the investigator, is plausibly close to
random. A process that assigns treatments in a highly nonrandom, inequitable
manner may, in rare and brief moments, assign aspects of treatments at random
or nearly so. Isolating those moments and aspects may extract a natural
experiment from a setting in which treatment assignment is otherwise quite
biased, far from random. Isolation is a tool that focuses on those rare, brief
instances, extracting a small natural experiment from otherwise useless data.
We discuss the theory behind isolation and illustrate its use in a reanalysis
of a well-known study of the effects of fertility on workforce participation.
Whether a woman becomes pregnant at a certain moment in her life and whether
she brings that pregnancy to term may reflect her aspirations for family,
education and career, the degree of control she exerts over her fertility, and
the quality of her relationship with the father; moreover, these aspirations
and relationships are unlikely to be recorded with precision in surveys and
censuses, and they may confound studies of workforce participation. However,
given that a women is pregnant and will bring the pregnancy to term, whether
she will have twins or a single child is, to a large extent, simply luck. Given
that a woman is pregnant at a certain moment, the differential comparison of
two types of pregnancies on workforce participation, twins or a single child,
may be close to randomized, not biased by unmeasured aspirations. In this
comparison, we find in our case study that mothers of twins had more children
but only slightly reduced workforce participation, approximately 5% less time
at work for an additional child.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS770 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Cross-screening in observational studies that test many hypotheses
We discuss observational studies that test many causal hypotheses, either
hypotheses about many outcomes or many treatments. To be credible an
observational study that tests many causal hypotheses must demonstrate that its
conclusions are neither artifacts of multiple testing nor of small biases from
nonrandom treatment assignment. In a sense that needs to be defined carefully,
hidden within a sensitivity analysis for nonrandom assignment is an enormous
correction for multiple testing: in the absence of bias, it is extremely
improbable that multiple testing alone would create an association insensitive
to moderate biases. We propose a new strategy called "cross-screening",
different from but motivated by recent work of Bogomolov and Heller on
replicability. Cross-screening splits the data in half at random, uses the
first half to plan a study carried out on the second half, then uses the second
half to plan a study carried out on the first half, and reports the more
favorable conclusions of the two studies correcting using the Bonferroni
inequality for having done two studies. If the two studies happen to concur,
then they achieve Bogomolov-Heller replicability; however, importantly,
replicability is not required for strong control of the family-wise error rate,
and either study alone suffices for firm conclusions. In randomized studies
with a few hypotheses, cross-split screening is not an attractive method when
compared with conventional methods of multiplicity control, but it can become
attractive when hundreds or thousands of hypotheses are subjected to
sensitivity analyses in an observational study. We illustrate the technique by
comparing 46 biomarkers in individuals who consume large quantities of fish
versus little or no fish.Comment: 33 pages, 2 figures, 5 table
Design of a 12 channel fm microwave receiver
The design, fabrication, and performance of elements of a low cost FM microwave satellite ground station receiver is described. It is capable of accepting 12 contiguous color television equivalent bandwidth channels in the 11.72 to 12.2 GHz band. Each channel is 40 MHz wide and incorporates a 4 MHz guard band. The modulation format is wideband FM and the channels are frequency division multiplexed. Twelve independent CATV compatible baseband outputs are provided. The overall system specifications are first discussed, then consideration is given to the receiver subsystems and the signal branching network
Comment: The Place of Death in the Quality of Life
Comment on The Place of Death in the Quality of Life [math.ST/0612783]Comment: Published at http://dx.doi.org/10.1214/088342306000000277 in the
Statistical Science (http://www.imstat.org/sts/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Mucking Out the Stalls: How KRS § 230.357 Promises to Change Custom and Facilitate Economic Efficiency in the Horse Industry
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