What do Bayesian methods offer population forecasters?

The Bayesian approach has a number of attractive properties for probabilistic forecasting. In this paper, we apply Bayesian time series models to obtain future population estimates with uncertainty for England and Wales. To account for heterogeneity found in the historical data, we add parameters to represent the stochastic volatility in the error terms. Uncertainty in model choice is incorporated through Bayesian model averaging techniques. The resulting predictive distributions from Bayesian forecasting models have two main advantages over those obtained using traditional stochastic models. Firstly, data and uncertainties in the parameters and model choice are explicitly included using probability distributions. As a result, more realistic probabilistic population forecasts can be obtained. Second, Bayesian models formally allow the incorporation of expert opinion, including uncertainty, into the forecast. Our results are discussed in relation to classical time series methods and existing cohort component projections. This paper demonstrates the flexibility of the Bayesian approach to simple population forecasting and provides insights into further developments of more complicated population models that include, for example, components of demographic change

Integrated Modelling of European Migration: Background, specification and results

The aims of this paper are to present the background and specification of the Integrated Modelling of European Migration (IMEM) model. Currently, international migration data are collected by individual countries with separate collection systems and designs. This creates problems when attempting to understand or predict population movements between countries as the reported data are inconsistent in terms of their availability, definitions and quality. Rather than wait for countries to harmonise their migration data collection and reporting systems, we propose a model to overcome the limitations of the various data sources. In particular, we propose a Bayesian model for harmonising and correcting the inadequacies in the available data and for estimating the completely missing flows. The focus is on estimating recent international migration flows amongst countries in the European Union (EU) and European Free Trade Association (EFTA) from 2002 to 2008, using data collected by Eurostat and other national and international institutions. We also include additional information provided by experts on the effects of undercount, measurement and accuracy. The methodology is integrated and capable of providing a synthetic data base with measures of uncertainty for international migration flows and other model parameters.

Modelling final outcome and length of call sequence to improve efficiency in interviewer call scheduling

Survey practitioners are increasingly interested in how best to use paradata to improve data collection processes. One particular question is if it is possible to identify early on during fieldwork sample cases that may require a long time, and therefore a lot of financial and staff resources, until interviewing is completed. More specifically, we aim to identify cases with long unsuccessful call sequences. This paper models call record data predicting final call outcome and length of a call sequence. Separate binary and joint multinomial logistic models for the two outcomes are presented, accounting for the clustering of households within interviewers. Of particular interest is to identify explanatory variables that predict final outcome and length of a call sequence. The study uses data from Understanding Society, a large-scale UK longitudinal survey. The work has implications for responsive and adaptive survey designs. The results indicate that modelling outcome and length of a call sequence jointly improves the fit of the model. Outcomes of previous calls, in particular from the most recent call, are highly predictive. The timing of calls and interviewer observation variables, although significant in the models, only slightly improve the predictive power

Using prior wave information and paradata: Can they help to predict response outcomes and call sequence length in a longitudinal study?

In recent years the use of paradata for nonresponse investigations has risen significantly. One key question is how useful paradata, including call record data and interviewer observations, from the current and previous waves of a longitudinal study, as well as previous wave survey information, are in predicting response outcomes in a longitudinal context. This paper aims to address this question. Final response outcome and sequence length (the number of calls/visits to a household) are modelled both separately and jointly for a longitudinal study. Being able to predict length of call sequence and response can help to improve both adaptive and responsive survey designs and to increase efficiency and effectiveness of call scheduling. The paper also identifies the impact of different methodological specifications of the models, for example different specifications of the response outcomes. Latent class analysis is used as one of the approaches to summarise call outcomes in sequences. To assess and compare the models in their ability to predict, indicators derived from classification tables, ROC (Receiver Operating Curves), discrimination and prediction are proposed in addition to the standard approach of using the pseudo R2 value, which is not a sufficient indicator on its own. The study uses data from Understanding Society, a large-scale longitudinal survey in the UK. The findings indicate that basic models (including geographic, design and survey data from the previous wave), although commonly used in predicting and adjusting for nonresponse, do not predict the response outcome well. Conditioning on previous wave paradata, including call record data, interviewer observation data and indicators of change, improve the fit of the models. A significant improvement can be observed when conditioning on the most recent call outcome, which may indicate that the nonresponse process predominantly depends on the most current circumstances of a sample unit

Augmenting migration statistics with expert knowledge

International migration statistics vary considerably from one country to another in terms of measurement, quality and coverage. Furthermore, immigration tend to be captured more accurately than emigration. In this paper, we first describe the need to augment reported flows of international migration with knowledge gained from experts on the measurement of migration statistics, obtained from a multi-stage Delphi survey. Second, we present our methodology for translating this information into prior distributions for input into the Integrated Modelling of European Migration (IMEM) model, which is designed to estimate migration flows amongst countries in the European Union (EU) and European Free Trade Association (EFTA), by using recent data collected by Eurostat and other national and international institutions. The IMEM model is capable of providing a synthetic data base with measures of uncertainty for international migration flows and other model parameters.

Measurement of low‐density lipoprotein cholesterol levels in primary and secondary prevention patients: Insights from the PALM registry

Background The 2013 American College of Cardiology/American Heart Association Guideline on the Treatment of Blood Cholesterol to Reduce Atherosclerotic Cardiovascular Risk in Adults recommended testing low-density lipoprotein cholesterol ( LDL -C) to identify untreated patients with LDL -C ≥190 mg/dL, assess lipid-lowering therapy adherence, and consider nonstatin therapy. We sought to determine whether clinician lipid testing practices were consistent with these guidelines. Methods and Results The PALM (Patient and Provider Assessment of Lipid Management) registry enrolled primary and secondary prevention patients from 140 US cardiology, endocrinology, and primary care offices in 2015 and captured demographic data, lipid treatment history, and the highest LDL -C level in the past 2 years. Core laboratory lipid levels were drawn at enrollment. Among 7627 patients, 2787 (36.5%) had no LDL -C levels measured in the 2 years before enrollment. Patients without chart-documented LDL -C levels were more often women, nonwhite, uninsured, and non-college graduates (all P\u3c0.01). Patients without prior lipid testing were less likely to receive statin treatment (72.6% versus 76.0%; P=0.0034), a high-intensity statin (21.5% versus 24.3%; P=0.016), nonstatin lipid-lowering therapy (24.8% versus 27.3%; P=0.037), and had higher core laboratory LDL -C levels at enrollment (median 97 versus 92 mg/dL; P\u3c0.0001) than patients with prior LDL -C testing. Of 166 individuals with core laboratory LDL -C levels ≥190 mg/dL, 36.1% had no LDL -C measurement in the prior 2 years, and 57.2% were not on a statin at the time of enrollment. Conclusions In routine clinical practice, LDL -C testing is associated with higher-intensity lipid-lowering treatment and lower achieved LDL -C level

On being the right size as an animal with plastids

Plastids typically reside in plant or algal cells—with one notable exception. There is one group of multicellular animals, sea slugs in the order Sacoglossa, members of which feed on siphonaceous algae. The slugs sequester the ingested plastids in the cytosol of cells in their digestive gland, giving the animals the color of leaves. In a few species of slugs, including members of the genus Elysia, the stolen plastids (kleptoplasts) can remain morphologically intact for weeks and months, surrounded by the animal cytosol, which is separated from the plastid stroma by only the inner and outer plastid membranes. The kleptoplasts of the Sacoglossa are the only case described so far in nature where plastids interface directly with the metazoan cytosol. That makes them interesting in their own right, but it has also led to the idea that it might someday be possible to engineer photosynthetic animals. Is that really possible? And if so, how big would the photosynthetic organs of such animals need to be? Here we provide two sets of calculations: one based on a best case scenario assuming that animals with kleptoplasts can be, on a per cm2 basis, as efficient at CO2 fixation as maize leaves, and one based on14 CO2 fixation rates measured in plastid-bearing sea slugs. We also tabulate an overview of the literature going back to 1970 reporting direct measurements or indirect estimates of the CO2 fixing capabilities of Sacoglossan slugs with plastids