Methods for Combining Probability and Nonprobability Samples Under Unknown Overlaps

Nonprobability (convenience) samples are increasingly sought to stabilize estimations for one or more population variables of interest that are performed using a randomized survey (reference) sample by increasing the effective sample size. Estimation of a population quantity derived from a convenience sample will typically result in bias since the distribution of variables of interest in the convenience sample is different from the population. A recent set of approaches estimates conditional (on sampling design predictors) inclusion probabilities for convenience sample units by specifying reference sample-weighted pseudo likelihoods. This paper introduces a novel approach that derives the propensity score for the observed sample as a function of conditional inclusion probabilities for the reference and convenience samples as our main result. Our approach allows specification of an exact likelihood for the observed sample. We construct a Bayesian hierarchical formulation that simultaneously estimates sample propensity scores and both conditional and reference sample inclusion probabilities for the convenience sample units. We compare our exact likelihood with the pseudo likelihoods in a Monte Carlo simulation study.Comment: 32 pages, 8 figure

The Prediction Properties of Inverse and Reverse Regression for the Simple Linear Calibration Problem

The calibration of measurement systems is a fundamental but under-studied problem within industrial statistics. The origins of this problem go back to basic chemical analysis based on NIST standards. In today's world these issues extend to mechanical, electrical, and materials engineering. Often, these new scenarios do not provide "gold standards" such as the standard weights provided by NIST. This paper considers the classic "forward regression followed by inverse regression" approach. In this approach the initial experiment treats the "standards" as the regressor and the observed values as the response to calibrate the instrument. The analyst then must invert the resulting regression model in order to use the instrument to make actual measurements in practice. This paper compares this classical approach to "reverse regression," which treats the standards as the response and the observed measurements as the regressor in the calibration experiment. Such an approach is intuitively appealing because it avoids the need for the inverse regression. However, it also violates some of the basic regression assumptions

Precise interpolar phasing of abrupt climate change during the last ice age

The last glacial period exhibited abrupt Dansgaard–Oeschger climatic oscillations, evidence of which is preserved in a variety of Northern Hemisphere palaeoclimate archives¹. Ice cores show that Antarctica cooled during the warm phases of the Greenland Dansgaard–Oeschger cycle and vice versa[superscript 2,3], suggesting an interhemispheric redistribution of heat through a mechanism called the bipolar seesaw[superscript 4–6]. Variations in the Atlantic meridional overturning circulation (AMOC) strength are thought to have been important, but much uncertainty remains regarding the dynamics and trigger of these abrupt events[superscript 7–9]. Key information is contained in the relative phasing of hemispheric climate variations, yet the large, poorly constrained difference between gas age and ice age and the relatively low resolution of methane records from Antarctic ice cores have so far precluded methane-based synchronization at the required sub-centennial precision[superscript 2,3,10]. Here we use a recently drilled high-accumulation Antarctic ice core to show that, on average, abrupt Greenland warming leads the corresponding Antarctic cooling onset by 218 ± 92 years (2σ) for Dansgaard–Oeschger events, including the Bølling event; Greenland cooling leads the corresponding onset of Antarctic warming by 208 ± 96 years. Our results demonstrate a north-to-south directionality of the abrupt climatic signal, which is propagated to the Southern Hemisphere high latitudes by oceanic rather than atmospheric processes. The similar interpolar phasing of warming and cooling transitions suggests that the transfer time of the climatic signal is independent of the AMOC background state. Our findings confirm a central role for ocean circulation in the bipolar seesaw and provide clear criteria for assessing hypotheses and model simulations of Dansgaard–Oeschger dynamics

The Complete Plastid Genome of Lagerstroemia fauriei and Loss of rpl2 Intron from Lagerstroemia (Lythraceae).

Lagerstroemia (crape myrtle) is an important plant genus used in ornamental horticulture in temperate regions worldwide. As such, numerous hybrids have been developed. However, DNA sequence resources and genome information for Lagerstroemia are limited, hindering evolutionary inferences regarding interspecific relationships. We report the complete plastid genome of Lagerstroemia fauriei. To our knowledge, this is the first reported whole plastid genome within Lythraceae. This genome is 152,440 bp in length with 38% GC content and consists of two single-copy regions separated by a pair of 25,793 bp inverted repeats. The large single copy and the small single copy regions span 83,921 bp and 16,933 bp, respectively. The genome contains 129 genes, including 17 located in each inverted repeat. Phylogenetic analysis of genera sampled from Geraniaceae, Myrtaceae, and Onagraceae corroborated the sister relationship between Lythraceae and Onagraceae. The plastid genomes of L. fauriei and several other Lythraceae species lack the rpl2 intron, which indicating an early loss of this intron within the Lythraceae lineage. The plastid genome of L. fauriei provides a much needed genetic resource for further phylogenetic research in Lagerstroemia and Lythraceae. Highly variable markers were identified for application in phylogenetic, barcoding and conservation genetic applications