Testing for the appropriate level of clustering in linear regression models

The overwhelming majority of empirical research that uses cluster-robust inference assumes that the clustering structure is known, even though there are often several possible ways in which a dataset could be clustered. We propose two tests for the correct level of clustering in regression models. One test focuses on inference about a single coefficient, and the other on inference about two or more coefficients. We provide both asymptotic and wild bootstrap implementations. The proposed tests work for a null hypothesis of either no clustering or ``fine'' clustering against alternatives of ``coarser'' clustering. We also propose a sequential testing procedure to determine the appropriate level of clustering. Simulations suggest that the bootstrap tests perform very well under the null hypothesis and can have excellent power. An empirical example suggests that using the tests leads to sensible inferences

Assessing the cumulative effect of long-term training load on the risk of injury in team sports

Objectives: Determine how to assess the cumulative effect of training load on the risk of injury or health problems in team sports. Methods: First, we performed a simulation based on a Norwegian Premier League male football dataset (n players=36). Training load was sampled from daily session rating of perceived exertion (sRPE). Different scenarios of the effect of sRPE on injury risk and the effect of relative sRPE on injury risk were simulated. These scenarios assumed that the probability of injury was the result of training load exposures over the previous 4 weeks. We compared seven different methods of modelling training load in their ability to model the simulated relationship. We then used the most accurate method, the distributed lag non-linear model (DLNM), to analyse data from Norwegian youth elite handball players (no. of players=205, no. of health problems=471) to illustrate how assessing the cumulative effect of training load can be done in practice. Results: DLNM was the only method that accurately modelled the simulated relationships between training load and injury risk. In the handball example, DLNM could show the cumulative effect of training load and how much training load affected health problem risk depending on the distance in time since the training load exposure. Conclusion: DLNM can be used to assess the cumulative effect of training load on injury risk.publishedVersio

Molecular characterization of a long range haplotype affecting protein yield and mastitis susceptibility in Norwegian Red cattle

<p>Abstract</p> <p>Background</p> <p>Previous fine mapping studies in Norwegian Red cattle (NRC) in the region 86-90.4 Mb on <it>Bos taurus </it>chromosome 6 (BTA6) has revealed a quantitative trait locus (QTL) for protein yield (PY) around 88 Mb and a QTL for clinical mastitis (CM) around 90 Mb. The close proximity of these QTLs may partly explain the unfavorable genetic correlation between these two traits in NRC. A long range haplotype covering this region was introduced into the NRC population through the importation of a Holstein-Friesian bull (1606 Frasse) from Sweden in the 1970s. It has been suggested that this haplotype has a favorable effect on milk protein content but an unfavorable effect on mastitis susceptibility. Selective breeding for milk production traits is likely to have increased the frequency of this haplotype in the NRC population.</p> <p>Results</p> <p>Association mapping for PY and CM in NRC was performed using genotypes from 556 SNPs throughout the region 86-97 Mb on BTA6 and daughter-yield-deviations (DYDs) from 2601 bulls made available from the Norwegian dairy herd recording system. Highest test scores for PY were found for single-nucleotide polymorphisms (SNPs) within and surrounding the genes <it>CSN2 </it>and <it>CSN1S2</it>, coding for the β-casein and α_S2-casein proteins. High coverage re-sequencing by high throughput sequencing technology enabled molecular characterization of a long range haplotype from 1606 Frasse encompassing these two genes. Haplotype analysis of a large number of descendants from this bull indicated that the haplotype was not markedly disrupted by recombination in this region. The haplotype was associated with both increased milk protein content and increased susceptibility to mastitis, which might explain parts of the observed genetic correlation between PY and CM in NRC. Plausible causal polymorphisms affecting PY were detected in the promoter region and in the 5'-flanking UTR of <it>CSN1S2</it>. These polymorphisms could affect transcription or translation of <it>CSN1S2 </it>and thereby affect the amount of α_S2-casein in milk.</p> <p>Highest test scores for CM were found in the region 89-91 Mb on BTA6, very close to a cluster of genes coding for CXC chemokines. Expression levels of some of these CXC chemokines have previously been shown to increase in bovine mammary gland cell lines after exposure to bacterial cell wall components.</p> <p>Conclusion</p> <p>Molecular characterization of the long range haplotype from the Holstein-Friesian bull 1606 Frasse, imported into NRC in the 1970s, revealed polymorphisms that could affect transcription or translation of the casein gene <it>CSN1S2</it>. Sires with this haplotype had daughters with significantly elevated milk protein content and selection for milk production traits is likely to have increased the frequency of this haplotype in the NRC population. The haplotype was also associated with increased mastitis susceptibility, which might explain parts of the genetic correlation between PY and CM in NRC.</p

The inclusion of sprints in low-intensity sessions during the transition period of elite cyclists improves endurance performance 6 weeks into the subsequent preparatory period

acceptedVersio

A new statistical approach to training load and injury risk: separating the acute from the chronic load

The relationship between recent (acute) training load relative to long-term (chronic) training load may be associated with sports injury risk. We explored the potential for modelling acute and chronic loads separately to address current statistical methodology limitations. We also determined whether there was any evidence of an interaction in the association between acute and chronic training loads and injury risk in football. A men’s Qatar Stars League football cohort (1 465 players, 1 977 injuries), where training load was defined as the number of minutes of activity, and a Norwegian elite U-19 football cohort (81 players, 60 injuries), where training load was defined as the session rating of perceived exertion (sRPE). Mixed logistic regression was run with training load on the current day (acute load) and cumulative past training load estimated by distributed lag non-linear models (chronic load) as independent variables. Injury was the outcome. An interaction between acute and chronic training load was modelled. In both football populations, we observed that the risk of injury on the current day for different values of acute training load was highest for players with low chronic load, followed by high and then medium chronic load. The slopes varied substantially between different levels of chronic training load, indicating an interaction. Modelling acute and chronic loads separately in regression models is a suitable statistical approach for analysing the association between relative training load and injury risk in injury prevention research. Sports scientists should also consider the potential for interactions between acute and chronic load.publishedVersio

Examining pelagic carbonate-rich sediments as an archive for authigenic uranium and molybdenum isotopes using reductive cleaning and leaching experiments

Novel metal isotope systematics are increasingly used to understand environmental change in geological history. On a global scale, the isotopic budgets of these metals respond to a range of environmental processes, allowing them to trace complex changes in the global climate system and carbon cycle. In particular, uranium (U) and molybdenum (Mo) isotopes are useful tools for quantifying the global extent of oceanic anoxia and euxinia respectively. The oceanic signature of these metals is recorded in contemporaneous marine sediments. Whilst, traditionally, organic-rich anoxic ‘black shales’ have provided a useful archive of these metals, carbonate sediments are increasingly being used as a passive recorder of ocean chemistry. The majority of published U and Mo isotope studies come from shallow water platform environments. By contrast, pelagic carbonate sediments are an under-explored archive for these metals, yet are widely available for important periods of Earth history. Despite their advantages, carbonates are a complex archive, containing multiple ‘contaminant’ components such as Mn-oxides, organic matter and detrital minerals. Each of these phases can have different metal concentrations and isotopic signatures, giving the potential to distort or bias the true oceanic signature recorded by the carbonate. Reductive cleaning procedures and selective leaching protocols can be used to avoid these contaminant phases, and are tested here on modern and ancient samples to judge their efficacy in isolating a ‘carbonate-bound fraction’. To this end, leaching experiments were performed using different concentration acetic acid, HCl and HNO3, on reductively cleaned and uncleaned sample pairs. The data demonstrate that Mn-oxide coatings and exchangeable phases have a large impact on the Mo isotopic signature (δ98Mo) of carbonates, even when weak leaching techniques are used to preferentially dissolve them. Furthermore, detrital sources of Mo are also easy to liberate with different leaching protocols, and exert a significant control on leachate isotopic composition. The leaching studies identify that the pelagic carbonate end-member has a relatively high δ98Mo, but the precise relationship to seawater compositions remains unclear. For U, significant contributions from non‑carbonate phases can clearly be identified in higher concentration leaching acids using U/Ca ratios. However, U isotopes (δ238U) show no resolvable difference with different leaching procedures and are not affected by reductive cleaning. This result probably reflects (a) the low potential for leaching refractory residual detrital U phases (e.g., zircon) that contain the majority of U in the sample and (b) the low U inventories of Mn oxides versus those of Mo. Instead, leaching likely extracts U that is mineralogically bound in carbonates and authigenic clays, which share a common isotopic signature. These new data suggest that U incorporation into pelagic carbonates may be dominated by adsorption, and be offset from seawater by ~−0.15‰, in a similar manner to that seen for clays

Transparency of Regulatory Data across the European Medicines Agency, Health Canada, and US Food and Drug Administration

Based on an analysis of relevant laws and policies, regulator data portals, and information requests, we find that clinical data, including clinical study reports, submitted to the European Medicines Agency and Health Canada to support approval of medicines are routinely made publicly available

Genetic variants associated with two major bovine milk fatty acids offer opportunities to breed for altered milk fat composition

publishedVersio