Generalizations of Current Status Data With Applications

In estimation of a survival function, current status data arises when the only information available on individuals is their survival status at a single monitoring time. Here we briefly review extensions of this form of data structure in two directions: (i) doubly censored current status data, where there is incomplete information on the origin of the failure time random variable, and (ii) current status information on more complicated stochastic processes. Simple examples of these data forms are presented for motivation.

Efficiency of the Sieved-NPMLE in CAR-Missing Data Models

We consider nonparametric missing data models for which the censoring mechanism satisfies coarsening at random and which allow complete observations on the variable X of interest. W show that beyond some empirical process conditions the only essential condition for efficiency of an NPMLE of the distribution of X is that the regions associated with incomplete observations on X contain enough complete observations. This is heuristically explained by describing the EM-algorithm. We provide identifiably of the self-consistency equation and efficiency of the NPMLE in order to make this statement rigorous. The usual kind of differentiability conditions in the proof are avoided by using an identity which holds for the NPMLE of linear parameters in convex models. We provide a bivariate censoring application in which the condition and hence the NPMLE fails, but where other estimators, not based on the NPMLE principle, are highly inefficient. It is shown how to slightly reduce the data so that the conditions hold for the reduced data. The conditions are verified for the univariate censoring, double censored, and Ibragimov-Has'minski models.

Integrated data acquisition and processing to determine metabolite contents, relaxation times, and macromolecule baseline in single examinations of individual subjects

Absolute quantitation of clinical (1)H-MR spectra is virtually always incomplete for single subjects because the separate determination of spectrum, baseline, and transverse and longitudinal relaxation times in single subjects is prohibitively long. Integrated Processing and Acquisition of Data (IPAD) based on a combined 2-dimensional experimental and fitting strategy is suggested to substantially improve the information content from a given measurement time. A series of localized saturation-recovery spectra was recorded and combined with 2-dimensional prior-knowledge fitting to simultaneously determine metabolite T(1) (from analysis of the saturation-recovery time course), metabolite T(2) (from lineshape analysis based on metabolite and water peak shapes), macromolecular baseline (based on T(1) differences and analysis of the saturation-recovery time course), and metabolite concentrations (using prior knowledge fitting and conventional procedures of absolute standardization). The procedure was tested on metabolite solutions and applied in 25 subjects (15-78 years old). Metabolite content was comparable to previously found values. Interindividual variation was larger than intraindividual variation in repeated spectra for metabolite content as well as for some relaxation times. Relaxation times were different for various metabolite groups. Parts of the interindividual variation could be explained by significant age dependence of relaxation times.

Effects of erythropoiesis-stimulating agents on fatigue- and anaemia-related symptoms in cancer patients: systematic review and meta-analyses of published and unpublished data.

Background:Erythropoiesis-stimulating agents (ESAs) reduce the need for red blood cell transfusions; however, they increase the risk of thromboembolic events and mortality. The impact of ESAs on quality of life (QoL) is controversial and led to different recommendations of medical societies and authorities in the USA and Europe. We aimed to critically evaluate and quantify the effects of ESAs on QoL in cancer patients.Methods:We included data from randomised controlled trials (RCTs) on the effects of ESAs on QoL in cancer patients. Randomised controlled trials were identified by searching electronic data bases and other sources up to January 2011. To reduce publication and outcome reporting biases, we included unreported results from clinical study reports. We conducted meta-analyses on fatigue- and anaemia-related symptoms measured with the Functional Assessment of Cancer Therapy-Fatigue (FACT-F) and FACT-Anaemia (FACT-An) subscales (primary outcomes) or other validated instruments.Results:We identified 58 eligible RCTs. Clinical study reports were available for 27% (4 out of 15) of the investigator-initiated trials and 95% (41 out of 43) of the industry-initiated trials. We excluded 21 RTCs as we could not use their QoL data for meta-analyses, either because of incomplete reporting (17 RCTs) or because of premature closure of the trial (4 RCTs). We included 37 RCTs with 10 581 patients; 21 RCTs were placebo controlled. Chemotherapy was given in 27 of the 37 RCTs. The median baseline haemoglobin (Hb) level was 10.1 g dl(-1); in 8 studies ESAs were stopped at Hb levels below 13 g dl(-1) and in 27 above 13 g dl(-1). For FACT-F, the mean difference (MD) was 2.41 (95% confidence interval (95% CI) 1.39-3.43; P<0.0001; 23 studies, n=6108) in all cancer patients and 2.81 (95% CI 1.73-3.90; P<0.0001; 19 RCTs, n=4697) in patients receiving chemotherapy, which was below the threshold (⩾3) for a clinically important difference (CID). Erythropoiesis-stimulating agents had a positive effect on anaemia-related symptoms (MD 4.09; 95% CI 2.37-5.80; P=0.001; 14 studies, n=2765) in all cancer patients and 4.50 (95% CI 2.55-6.45; P<0.0001; 11 RCTs, n=2436) in patients receiving chemotherapy, which was above the threshold (⩾4) for a CID. Of note, this effect persisted when we restricted the analysis to placebo-controlled RCTs in patients receiving chemotherapy. There was some evidence that the MDs for FACT-F were above the threshold for a CID in RCTs including cancer patients receiving chemotherapy with Hb levels below 12 g dl(-1) at baseline and in RCTs stopping ESAs at Hb levels above 13 g dl(-1). However, these findings for FACT-F were not confirmed when we restricted the analysis to placebo-controlled RCTs in patients receiving chemotherapy.Conclusions:In cancer patients, particularly those receiving chemotherapy, we found that ESAs provide a small but clinically important improvement in anaemia-related symptoms (FACT-An). For fatigue-related symptoms (FACT-F), the overall effect did not reach the threshold for a CID.British Journal of Cancer advance online publication, 17 April 2014; doi:10.1038/bjc.2014.171 www.bjcancer.com.

Comparison of noninferiority margins reported in protocols and publications showed incomplete and inconsistent reporting.

OBJECTIVES To compare noninferiority margins defined in study protocols and trial registry records with margins reported in subsequent publications. STUDY DESIGN AND SETTING Comparison of protocols of noninferiority trials submitted 2001 to 2005 to ethics committees in Switzerland and The Netherlands with corresponding publications and registry records. We searched MEDLINE via PubMed, the Cochrane Controlled Trials Register (Cochrane Library issue 01/2012), and Google Scholar in September 2013 to identify published reports, and the International Clinical Trials Registry Platform of the World Health Organization in March 2013 to identify registry records. Two readers recorded the noninferiority margin and other data using a standardized data-abstraction form. RESULTS The margin was identical in study protocol and publication in 43 (80%) of 54 pairs of study protocols and articles. In the remaining pairs, reporting was inconsistent (five pairs, 9%), or the noninferiority margin was either not reported in the publication (five pairs, 9%) or not defined in the study protocol (one pair). The confidence interval or the exact P-value required to judge whether the result was compatible with noninferior, inferior, or superior efficacy was reported in 43 (80%) publications. Complete and consistent reporting of both noninferiority margin and confidence interval (or exact P-value) was present in 39 (72%) protocol-publication pairs. Twenty-nine trials (54%) were registered in trial registries, but only one registry record included the noninferiority margin. CONCLUSION The reporting of noninferiority margins was incomplete and inconsistent with study protocols in a substantial proportion of published trials, and margins were rarely reported in trial registries.

Reporting and handling missing outcome data in mental health: a systematic review of Cochrane systematic reviews and meta-analyses

OBJECTIVES The purpose of the study was to provide empirical evidence about the reporting of methodology to address missing outcome data and the acknowledgement of their impact in Cochrane systematic reviews in the mental health field. METHODS Systematic reviews published in the Cochrane Database of Systematic Reviews after January 1, 2009 by three Cochrane Review Groups relating to mental health were included. RESULTS One hundred ninety systematic reviews were considered. Missing outcome data were present in at least one included study in 175 systematic reviews. Of these 175 systematic reviews, 147 (84%) accounted for missing outcome data by considering a relevant primary or secondary outcome (e.g., dropout). Missing outcome data implications were reported only in 61 (35%) systematic reviews and primarily in the discussion section by commenting on the amount of the missing outcome data. One hundred forty eligible meta-analyses with missing data were scrutinized. Seventy-nine (56%) of them had studies with total dropout rate between 10 and 30%. One hundred nine (78%) meta-analyses reported to have performed intention-to-treat analysis by including trials with imputed outcome data. Sensitivity analysis for incomplete outcome data was implemented in less than 20% of the meta-analyses. CONCLUSIONS Reporting of the techniques for handling missing outcome data and their implications in the findings of the systematic reviews are suboptimal.

Justification of Data Warehousing Projects

Project justification is regarded as one of the major methodological deficits in Data Warehousing practice. As reasons for applying inappropriate methods, performing incomplete evaluations, or even entirely omitting justifications, the special nature of Data Warehousing benefits and the large portion of infrastructure-related activities are stated. In this paper, the economic justification of Data Warehousing projects is analyzed, and first results from a large academiaindustry collaboration project in the field of non-technical issues of Data Warehousing are presented. As conceptual foundations, the role of the Data Warehouse system in corporate application architectures is analyzed, and the specific properties of Data Warehousing projects are discussed. Based on an applicability analysis of traditional approaches to economic IT project justification, basic steps and responsibilities for the justification of Data Warehousing projects are derived.

New algorithms for automated phylogenetic reconstruction using artificial intelligence and data mining techniques

Academic and industrial research in the late 90s have brought about an exponential explosion of DNA sequence data. Automated expert systems are being created to help biologists to extract patterns, trends and links from this ever-deepening ocean of information. Two such systems aimed on retrieving and subsequently utilizing phylogenetically relevant information have been developed in this dissertation, the major objective of which was to automate the often difficult and confusing phylogenetic reconstruction process. ^ Popular phylogenetic reconstruction methods, such as distance-based methods, attempt to find an optimal tree topology (that reflects the relationships among related sequences and their evolutionary history) by searching through the topology space. Various compromises between the fast (but incomplete) and exhaustive (but computationally prohibitive) search heuristics have been suggested. An intelligent compromise algorithm that relies on a flexible “beam” search principle from the Artificial Intelligence domain and uses the pre-computed local topology reliability information to adjust the beam search space continuously is described in the second chapter of this dissertation. ^ However, sometimes even a (virtually) complete distance-based method is inferior to the significantly more elaborate (and computationally expensive) maximum likelihood (ML) method. In fact, depending on the nature of the sequence data in question either method might prove to be superior. Therefore, it is difficult (even for an expert) to tell a priori which phylogenetic reconstruction method—distance-based, ML or maybe maximum parsimony (MP)—should be chosen for any particular data set. ^ A number of factors, often hidden, influence the performance of a method. For example, it is generally understood that for a phylogenetically “difficult” data set more sophisticated methods (e.g., ML) tend to be more effective and thus should be chosen. However, it is the interplay of many factors that one needs to consider in order to avoid choosing an inferior method (potentially a costly mistake, both in terms of computational expenses and in terms of reconstruction accuracy.) ^ Chapter III of this dissertation details a phylogenetic reconstruction expert system that selects a superior proper method automatically. It uses a classifier (a Decision Tree-inducing algorithm) to map a new data set to the proper phylogenetic reconstruction method. ^

Asset Pricing with Heterogeneous Agents, Incomplete Markets and Trading Constraints

The consumption capital asset pricing model is the standard economic model used to capture stock market behavior. However, empirical tests have pointed out to its inability to account quantitatively for the high average rate of return and volatility of stocks over time for plausible parameter values. Recent research has suggested that the consumption of stockholders is more strongly correlated with the performance of the stock market than the consumption of non-stockholders. We model two types of agents, non-stockholders with standard preferences and stock holders with preferences that incorporate elements of the prospect theory developed by Kahneman and Tversky (1979). In addition to consumption, stockholders consider fluctuations in their financial wealth explicitly when making decisions. Data from the Panel Study of Income Dynamics are used to calibrate the labor income processes of the two types of agents. Each agent faces idiosyncratic shocks to his labor income as well as aggregate shocks to the per-share dividend but markets are incomplete and agents cannot hedge consumption risks completely. In addition, consumers face both borrowing and short-sale constraints. Our results show that in equilibrium, agents hold different portfolios. Our model is able to generate a time-varying risk premium of about 5.5% while maintaining a low risk free rate, thus suggesting a plausible explanation for the equity premium puzzle reported by Mehra and Prescott (1985).

Estimating parameters in Markov models for longitudinal studies with missing data or surrogate outcomes

The discrete-time Markov chain is commonly used in describing changes of health states for chronic diseases in a longitudinal study. Statistical inferences on comparing treatment effects or on finding determinants of disease progression usually require estimation of transition probabilities. In many situations when the outcome data have some missing observations or the variable of interest (called a latent variable) can not be measured directly, the estimation of transition probabilities becomes more complicated. In the latter case, a surrogate variable that is easier to access and can gauge the characteristics of the latent one is usually used for data analysis. ^ This dissertation research proposes methods to analyze longitudinal data (1) that have categorical outcome with missing observations or (2) that use complete or incomplete surrogate observations to analyze the categorical latent outcome. For (1), different missing mechanisms were considered for empirical studies using methods that include EM algorithm, Monte Carlo EM and a procedure that is not a data augmentation method. For (2), the hidden Markov model with the forward-backward procedure was applied for parameter estimation. This method was also extended to cover the computation of standard errors. The proposed methods were demonstrated by the Schizophrenia example. The relevance of public health, the strength and limitations, and possible future research were also discussed. ^

Experiment: Growth rates and percentages of normal versus malformed versus incomplete versus incomplete and malformed coccoliths

The coccolithophore Emiliania huxleyi (Lohmann) W. W. Hay et H. Mohler was cultured in natural seawater with the addition of either the microtubule-inhibitor colchicine, the actin-inhibitor cytochalasin B, or the photosynthesis inhibitor 3-(3,4 dichlorophenyl)-1,1-dimethyl-urea (DCMU). Additionally, E. huxleyi was cultured at different light intensities and temperatures. Growth rate was monitored, and coccolith morphology analyzed. While every treatment affected growth rate, the percentage of malformed coccoliths increased with colchicine, cytochalasin B, and at higher than optimal temperature. These results represent the first experimental evidence for the role of microtubules and actin microfilaments in coccolith morphogenesis.

Geochemical data and magnetic measurements of IODP Expedition 308, Hole U1319A from the Gulf of Mexico

A 160 m mostly turbiditic late Pleistocene sediment sequence (IODP Expedition 308, Hole U1319A) from the Brazos-Trinity intraslope basin system off Texas was investigated with paleo- and rock magnetic methods. Numerous layers depleted in iron oxides and enriched by the ferrimagnetic iron-sulfide mineral greigite (Fe3S4) were detected by diagnostic magnetic properties. From the distribution of these layers, their stratigraphic context and the present geochemical zonation, we develop two conceptual reaction models of greigite formation in non-steady depositional environments. The "sulfidization model" predicts single or twin greigite layers by incomplete transformation of iron monosulfides with polysulfides around the sulfate methane transition (SMT). The "oxidation model" explains greigite formation by partial oxidation of iron monosulfides near the iron redox boundary during periods of downward shifting oxidation fronts. The stratigraphic record provides evidence that both these greigite formation processes act here at typical depths of about 12-14 mbsf and 3-4 mbsf. Numerous "fossil" greigite layers most likely preserved by rapid upward shifts of the redox zonation denote past SMT and sea floor positions characterized by stagnant hemipelagic sedimentation conditions. Six diagenetic stages from a pristine magnetite-dominated to a fully greigite-dominated magnetic mineralogy were differentiated by combination of various hysteresis and remanence parameters.

Gridded climate data from 5 Global Climate Models (GCM) of the Last Glacial Maximum (LGM) downscaled to 30 arc seconds for Europe, with links to NetCDF files

Studies on the impact of historical, current and future global change require very high-resolution climate data (less or equal 1km) as a basis for modelled responses, meaning that data from digital climate models generally require substantial rescaling. Another shortcoming of available datasets on past climate is that the effects of sea level rise and fall are not considered. Without such information, the study of glacial refugia or early Holocene plant and animal migration are incomplete if not impossible. Sea level at the last glacial maximum (LGM) was approximately 125m lower, creating substantial additional terrestrial area for which no current baseline data exist. Here, we introduce the development of a novel, gridded climate dataset for LGM that is both very high resolution (1km) and extends to the LGM sea and land mask. We developed two methods to extend current terrestrial precipitation and temperature data to areas between the current and LGM coastlines. The absolute interpolation error is less than 1°C and 0.5 °C for 98.9% and 87.8% of all pixels for the first two 1 arc degree distance zones. We use the change factor method with these newly assembled baseline data to downscale five global circulation models of LGM climate to a resolution of 1km for Europe. As additional variables we calculate 19 'bioclimatic' variables, which are often used in climate change impact studies on biological diversity. The new LGM climate maps are well suited for analysing refugia and migration during Holocene warming following the LGM.

Categorical Missing Data Imputation Using Fuzzy Neural Networks with Numerical and Categorical Inputs

There are many situations where input feature vectors are incomplete and methods to tackle the problem have been studied for a long time. A commonly used procedure is to replace each missing value with an imputation. This paper presents a method to perform categorical missing data imputation from numerical and categorical variables. The imputations are based on Simpson’s fuzzy min-max neural networks where the input variables for learning and classification are just numerical. The proposed method extends the input to categorical variables by introducing new fuzzy sets, a new operation and a new architecture. The procedure is tested and compared with others using opinion poll data.

Application of a Bayesian/Generalised Least-Squares method to generate correlations between independent neutron fission yield data

Fission product yields are fundamental parameters for several nuclear engineering calculations and in particular for burn-up/activation problems. The impact of their uncertainties was widely studied in the past and valuations were released, although still incomplete. Recently, the nuclear community expressed the need for full fission yield covariance matrices to produce inventory calculation results that take into account the complete uncertainty data. In this work, we studied and applied a Bayesian/generalised least-squares method for covariance generation, and compared the generated uncertainties to the original data stored in the JEFF-3.1.2 library. Then, we focused on the effect of fission yield covariance information on fission pulse decay heat results for thermal fission of 235U. Calculations were carried out using different codes (ACAB and ALEPH-2) after introducing the new covariance values. Results were compared with those obtained with the uncertainty data currently provided by the library. The uncertainty quantification was performed with the Monte Carlo sampling technique. Indeed, correlations between fission yields strongly affect the statistics of decay heat. Introduction Nowadays, any engineering calculation performed in the nuclear field should be accompanied by an uncertainty analysis. In such an analysis, different sources of uncertainties are taken into account. Works such as those performed under the UAM project (Ivanov, et al., 2013) treat nuclear data as a source of uncertainty, in particular cross-section data for which uncertainties given in the form of covariance matrices are already provided in the major nuclear data libraries. Meanwhile, fission yield uncertainties were often neglected or treated shallowly, because their effects were considered of second order compared to cross-sections (Garcia-Herranz, et al., 2010). However, the Working Party on International Nuclear Data Evaluation Co-operation (WPEC)