Molecular phylogenies map to biogeography better than morphological ones

Phylogenetic relationships are inferred principally from two classes of data: morphological and molecular. Most current phylogenies of extant taxa are inferred from molecules, and when morphological and molecular trees conflict the latter are often preferred. Although supported by simulations, the superiority of molecular trees has never been assessed empirically. Here we test phylogenetic accuracy using two independent data sources: biogeographical distributions and fossil first occurrences. For 48 pairs of morphological and molecular trees, we show that, on average, molecular trees provide a better fit to biogeographical data than their morphological counterparts, and that, biogeographical congruence increases over research time. We find no significant differences in stratigraphical congruence between morphological and molecular trees. These findings have implications for understanding homoplasy in morphological data sets, the utility of morphology as a test of molecular hypotheses, and the implications of analysing fossil groups for which molecular data are unavailable

Study design flaws and statistical challenges in evaluating fertility treatments

Health interventions should be tested before being introduced into clinical practice, to find out whether they work and whether they are harmful. However, research studies will only provide reliable answers to these questions if they are appropriately designed and analysed. But these are not trivial tasks. We review some methodological challenges that arise when evaluating fertility interventions and explain the implications for a non-statistical audience. These include flexibility in outcomes and analyses; use of surrogate outcomes instead of live birth; use of inappropriate denominators; evaluating cumulative outcomes and time to live birth; allowing each patient or couple to contribute to a research study more than once. We highlight recurring errors and present solutions. We conclude by highlighting the importance of collaboration between clinical and methodological experts, as well as people with experience of subfertility, for realising high-quality research