Estimating equations with nonignorably missing response data

Troxel, Lipsitz, and Brennan (1997, Biometrics 53, 857-869) considered parameter estimation from survey data with nonignorable nonresponse and proposed weighted estimating equations to remove the biases in the complete-case analysis that ignores missing observations. This paper suggests two alternative modifications for unbiased estimation of regression parameters when a binary outcome is potentially observed at successive time points. The weighting approach of Robins, Rotnitzky, and Zhao (1995, Journal of the American Statistical Association 90, 106-121) is also modified to obtain unbiased estimating functions. The suggested estimating functions are unbiased only when the missingness probability is correctly specified, and misspecification of the missingness model will result in biases in the estimates. Simulation studies are carried out to assess the performance of different methods when the covariate is binary or normal. For the simulation models used, the relative efficiency of the two new methods to the weighting methods is about 3.0 for the slope parameter and about 2.0 for the intercept parameter when the covariate is continuous and the missingness probability is correctly specified. All methods produce substantial biases in the estimates when the missingness model is misspecified or underspecified. Analysis of data from a medical survey illustrates the use and possible differences of these estimating functions.

EGFR expression as a predictor of survival for first-line chemotherapy plus cetuximab in patients with advanced non-small-cell lung cancer : analysis of data from the phase 3 FLEX study

Background: Findings from the phase 3 First-Line ErbituX in lung cancer (FLEX) study showed that the addition of cetuximab to first-line chemotherapy significantly improved overall survival compared with chemotherapy alone (hazard ratio [HR] 0·871, 95% CI 0·762-0·996; p=0·044) in patients with advanced non-small-cell lung cancer (NSCLC). To define patients benefiting most from cetuximab, we studied the association of tumour EGFR expression level with clinical outcome in FLEX study patients. Methods: We used prospectively collected tumour EGFR expression data to generate an immunohistochemistry score for FLEX study patients on a continuous scale of 0-300. We used response data to select an outcome-based discriminatory threshold immunohistochemistry score for EGFR expression of 200. Treatment outcome was analysed in patients with low (immunohistochemistry score <200) and high (≥200) tumour EGFR expression. The primary endpoint in the FLEX study was overall survival. We analysed patients from the FLEX intention-to-treat (ITT) population. The FLEX study is registered with ClinicalTrials.gov, number NCT00148798. Findings: Tumour EGFR immunohistochemistry data were available for 1121 of 1125 (99·6%) patients from the FLEX study ITT population. High EGFR expression was scored for 345 (31%) evaluable patients and low for 776 (69%) patients. For patients in the high EGFR expression group, overall survival was longer in the chemotherapy plus cetuximab group than in the chemotherapy alone group (median 12·0 months [95% CI 10·2-15·2] vs 9·6 months [7·6-10·6]; HR 0·73, 0·58-0·93; p=0·011), with no meaningful increase in side-effects. We recorded no corresponding survival benefit for patients in the low EGFR expression group (median 9·8 months [8·9-12·2] vs 10·3 months [9·2-11·5]; HR 0·99, 0·84-1·16; p=0·88). A treatment interaction test assessing the difference in the HRs for overall survival between the EGFR expression groups suggested a predictive value for EGFR expression (p=0·044). Interpretation: High EGFR expression is a tumour biomarker that can predict survival benefit from the addition of cetuximab to first-line chemotherapy in patients with advanced NSCLC. Assessment of EGFR expression could offer a personalised treatment approach in this setting. Funding: Merck KGaA. © 2012 Elsevier Ltd.

A biphasic response to adenosine in the coronary vasculature of the K+-arrested perfused rat heart

Biphasic vasodilatory responses to adenosine and 5'-N-ethylcarboxamidoadenosine (NECA) were observed in the coronary vasculature of K(+)-arrested perfused rat hearts. Dose-response data for both agonists were best represented by two-site models. For adenosine, two sites with negative log ED50 (pED50) values of 8.1 +/- 0.1 (mean +/- S.E.M) and 5.2 +/- 0.1 were obtained, mediating 31 +/- 2% and 69 +/- 2% of the total response. In the presence of 8-phenyltheophylline, the vasodilatory response to adenosine remained best fitted to a two-site model with pED50 values of 7.0 +/- 0.2 and 5.4 +/- 0.2. The relative contribution of each site to the total response remained unchanged. For NECA, pED50 values of 9.6 +/- 0.1 and 6.8 +/- 0.2 were obtained, representing 48 +/- 3% and 52 +/- 3% of the sites, respectively. In contrast, ATP produced a monophasic response with a pED50 value of 8.8 +/- 0.1. These results provide evidence of adenosine receptor and response heterogeneity in the in situ coronary vasculature.

Providing 'best practice' placements begins with mentoring skills : overview of the Program of Experience in the Palliative Approach (PEPA) quality improvement initiatives for mentors

Objectives PEPA is funded by the Department of Health and Ageing and aims to further improve the skill and confidence of the generalist workforce to work with people with palliative care needs. Recent quality improvement initiatives to promote transfer of learning into practice include appointment of a clinical educator, implementation of an online module for mentors and delivery of a mentoring workshop (collaborating with NSAP and PCC4U). This paper presents an overview of outcomes from these quality improvement initiatives. Methods PEPA host sites are selected based on their specialist palliative care level. Host site managers are surveyed six-monthly and participants are surveyed pre and three months post-placement to collect open and fixed response data on their experience of the program. Participants in the mentoring workshop (n=39) were asked to respond to a survey regarding the workshop outcomes. Results The percentage of placement participants who strongly agreed they ‘have the ability to implement the interventions required for people who have a life-limiting illness’ increased from 35% in 2011 (n=34) to 51% in 2012 (n=91) post-placement. Responses from mentor workshop participants indicated that 76% of respondents (n=25) agreed that they were able to identify principles for mentoring in the context of palliative care. In 2012, 61% of host site managers (n=54) strongly agreed that PEPA supports clinician working with people with a life-limiting illness. Conclusion Strategies to build the capabilities of palliative care professionals to mentor and support the learning experience of PEPA participants are critical to ongoing improvements of the program.

NESSTI : norms for environmental sound stimuli

In this paper we provide normative data along multiple cognitive and affective variable dimensions for a set of 110 sounds, including living and manmade stimuli. Environmental sounds are being increasingly utilized as stimuli in the cognitive, neuropsychological and neuroimaging fields, yet there is no comprehensive set of normative information for these type of stimuli available for use across these experimental domains. Experiment 1 collected data from 162 participants in an on-line questionnaire, which included measures of identification and categorization as well as cognitive and affective variables. A subsequent experiment collected response times to these sounds. Sounds were normalized to the same length (1 second) in order to maximize usage across multiple paradigms and experimental fields. These sounds can be freely downloaded for use, and all response data have also been made available in order that researchers can choose one or many of the cognitive and affective dimensions along which they would like to control their stimuli. Our hope is that the availability of such information will assist researchers in the fields of cognitive and clinical psychology and the neuroimaging community in choosing well-controlled environmental sound stimuli, and allow comparison across multiple studies.

Relationship between EGFR expression, EGFR mutation status, and the efficacy of chemotherapy plus cetuximab in FLEX study patients with advanced non-small-cell lung cancer

INTRODUCTION: The phase III FLEX study (NCT00148798) in advanced non-small-cell lung cancer indicated that the survival benefit associated with the addition of cetuximab to cisplatin and vinorelbine was limited to patients whose tumors expressed high levels of epidermal growth factor receptor (EGFR) (immunohistochemistry score of >/=200; scale 0-300). We assessed whether the treatment effect was also modulated in FLEX study patients by tumor EGFR mutation status. METHODS: A tumor mutation screen of EGFR exons 18 to 21 included 971 of 1125 (86%) FLEX study patients. Treatment outcome in low and high EGFR expression groups was analyzed across efficacy endpoints according to tumor EGFR mutation status. RESULTS: Mutations in EGFR exons 18 to 21 were detected in 133 of 971 tumors (14%), 970 of which were also evaluable for EGFR expression level. The most common mutations were exon 19 deletions and L858R (124 of 133 patients; 93%). In the high EGFR expression group (immunohistochemistry score of >/=200), a survival benefit for the addition of cetuximab to chemotherapy was demonstrated in patients with EGFR wild-type (including T790M mutant) tumors. Although patient numbers were small, those in the high EGFR expression group whose tumors carried EGFR mutations may also have derived a survival benefit from the addition of cetuximab to chemotherapy. Response data suggested a cetuximab benefit in the high EGFR expression group regardless of EGFR mutation status. CONCLUSIONS: The survival benefit associated with the addition of cetuximab to first-line chemotherapy for advanced non-small-cell lung cancer expressing high levels of EGFR is not limited by EGFR mutation status.

Stop-signal response inhibition in schizophrenia : Behavioural, event-related potential and functional neuroimaging data

Inhibitory control deficits are well documented in schizophrenia, supported by impairment in an established measure of response inhibition, the stop-signal reaction time (SSRT). We investigated the neural basis of this impairment by comparing schizophrenia patients and controls matched for age, sex and education on behavioural, functional magnetic resonance imaging (fMRI) and event-related potential (ERP) indices of stop-signal task performance. Compared to controls, patients exhibited slower SSRT and reduced right inferior frontal gyrus (rIFG) activation, but rIFG activation correlated with SSRT in both groups. Go stimulus and stop-signal ERP components (N1/P3) were smaller in patients, but the peak latencies of stop-signal N1 and P3 were also delayed in patients, indicating impairment early in stop-signal processing. Additionally, response-locked lateralised readiness potentials indicated response preparation was prolonged in patients. An inability to engage rIFG may predicate slowed inhibition in patients, however multiple spatiotemporal irregularities in the networks underpinning stop-signal task performance may contribute to this deficit.

Psychological predictors of the propensity to omit short-response items on a high-stakes achievement test

This article presents the findings of a study of the psychological variables that discriminate between high and low omitters on a high-stakes achievement test using a short-response format. Data were obtained from a questionnaire administered to a random sample (N = 1,908) of students prior to sitting the 1997 Queensland Core Skills (QCS) Test (N = 29,273). Fourteen psychological variables were measured including test anxiety (four subscales), emotional stability, achievement motivation, self-esteem, academic self-concept, self-estimate of ability, locus of control (three subscales), and approaches to learning (two subscales). The results were analyzed using descriptive discriminant analysis and suggested that the psychological predictors of the propensity to omit short-response items include test-irrelevant thinking and academic self-concept, with sex of candidate being a mediating variable.

Bayesian latent trait modeling of migraine symptom data

Definition of disease phenotype is a necessary preliminary to research into genetic causes of a complex disease. Clinical diagnosis of migraine is currently based on diagnostic criteria developed by the International Headache Society. Previously, we examined the natural clustering of these diagnostic symptoms using latent class analysis (LCA) and found that a four-class model was preferred. However, the classes can be ordered such that all symptoms progressively intensify, suggesting that a single continuous variable representing disease severity may provide a better model. Here, we compare two models: item response theory and LCA, each constructed within a Bayesian context. A deviance information criterion is used to assess model fit. We phenotyped our population sample using these models, estimated heritability and conducted genome-wide linkage analysis using Merlin-qtl. LCA with four classes was again preferred. After transformation, phenotypic trait values derived from both models are highly correlated (correlation = 0.99) and consequently results from subsequent genetic analyses were similar. Heritability was estimated at 0.37, while multipoint linkage analysis produced genome-wide significant linkage to chromosome 7q31-q33 and suggestive linkage to chromosomes 1 and 2. We argue that such continuous measures are a powerful tool for identifying genes contributing to migraine susceptibility.

The mechanical response of the ovine lumbar anulus fibrosus to uniaxial, biaxial and shear loads

Analytical and computational models of the intervertebral disc (IVD) are commonly employed to enhance understanding of the biomechanics of the human spine and spinal motion segments. The accuracy of these models in predicting physiological behaviour of the spine is intrinsically reliant on the accuracy of the material constitutive representations employed to represent the spinal tissues. There is a paucity of detailed mechanical data describing the material response of the reinforced­ground matrix in the anulus fibrosus of the IVD. In the present study, the ‘reinforced­ground matrix’ was defined as the matrix with the collagen fibres embedded but not actively bearing axial load, thus incorporating the contribution of the fibre-fibre and fibre-matrix interactions. To determine mechanical parameters for the anulus ground matrix, mechanical tests were carried out on specimens of ovine anulus, under unconfined uniaxial compression, simple shear and biaxial compression. Test specimens of ovine anulus fibrosus were obtained with an adjacent layer of vertebral bone/cartilage on the superior and inferior specimen surface. Specimen geometry was such that there were no continuous collagen fibres coupling the two endplates. Samples were subdivided according to disc region - anterior, lateral and posterior - to determine the regional inhomogeneity in the anulus mechanical response. Specimens were loaded at a strain rate sufficient to avoid fluid outflow from the tissue and typical stress-strain responses under the initial load application and under repeated loading were determined for each of the three loading types. The response of the anulus tissue to the initial and repeated load cycles was significantly different for all load types, except biaxial compression in the anterior anulus. Since the maximum applied strain exceeded the damage strain for the tissue, experimental results for repeated loading reflected the mechanical ability of the tissue to carry load, subsequent to the initiation of damage. To our knowledge, this is the first study to provide experimental data describing the response of the ‘reinforced­ground matrix’ to biaxial compression. Additionally, it is novel in defining a study objective to determine the regionally inhomogeneous response of the ‘reinforced­ground matrix’ under an extensive range of loading conditions suitable for mechanical characterisation of the tissue. The results presented facilitate the development of more detailed and comprehensive constitutive descriptions for the large strain nonlinear elastic or hyperelastic response of the anulus ground matrix.

Hierarchical models for 2D presence/absence data having ambiguous zeroes: With a biogeographical case study on dingo behaviour

This dissertation is primarily an applied statistical modelling investigation, motivated by a case study comprising real data and real questions. Theoretical questions on modelling and computation of normalization constants arose from pursuit of these data analytic questions. The essence of the thesis can be described as follows. Consider binary data observed on a two-dimensional lattice. A common problem with such data is the ambiguity of zeroes recorded. These may represent zero response given some threshold (presence) or that the threshold has not been triggered (absence). Suppose that the researcher wishes to estimate the effects of covariates on the binary responses, whilst taking into account underlying spatial variation, which is itself of some interest. This situation arises in many contexts and the dingo, cypress and toad case studies described in the motivation chapter are examples of this. Two main approaches to modelling and inference are investigated in this thesis. The first is frequentist and based on generalized linear models, with spatial variation modelled by using a block structure or by smoothing the residuals spatially. The EM algorithm can be used to obtain point estimates, coupled with bootstrapping or asymptotic MLE estimates for standard errors. The second approach is Bayesian and based on a three- or four-tier hierarchical model, comprising a logistic regression with covariates for the data layer, a binary Markov Random field (MRF) for the underlying spatial process, and suitable priors for parameters in these main models. The three-parameter autologistic model is a particular MRF of interest. Markov chain Monte Carlo (MCMC) methods comprising hybrid Metropolis/Gibbs samplers is suitable for computation in this situation. Model performance can be gauged by MCMC diagnostics. Model choice can be assessed by incorporating another tier in the modelling hierarchy. This requires evaluation of a normalization constant, a notoriously difficult problem. Difficulty with estimating the normalization constant for the MRF can be overcome by using a path integral approach, although this is a highly computationally intensive method. Different methods of estimating ratios of normalization constants (N Cs) are investigated, including importance sampling Monte Carlo (ISMC), dependent Monte Carlo based on MCMC simulations (MCMC), and reverse logistic regression (RLR). I develop an idea present though not fully developed in the literature, and propose the Integrated mean canonical statistic (IMCS) method for estimating log NC ratios for binary MRFs. The IMCS method falls within the framework of the newly identified path sampling methods of Gelman & Meng (1998) and outperforms ISMC, MCMC and RLR. It also does not rely on simplifying assumptions, such as ignoring spatio-temporal dependence in the process. A thorough investigation is made of the application of IMCS to the three-parameter Autologistic model. This work introduces background computations required for the full implementation of the four-tier model in Chapter 7. Two different extensions of the three-tier model to a four-tier version are investigated. The first extension incorporates temporal dependence in the underlying spatio-temporal process. The second extensions allows the successes and failures in the data layer to depend on time. The MCMC computational method is extended to incorporate the extra layer. A major contribution of the thesis is the development of a fully Bayesian approach to inference for these hierarchical models for the first time. Note: The author of this thesis has agreed to make it open access but invites people downloading the thesis to send her an email via the 'Contact Author' function.

Real-time performance modelling of a sustained attention to response task

Vigilance declines when exposed to highly predictable and uneventful tasks. Monotonous tasks provide little cognitive and motor stimulation and contribute to human errors. This paper aims to model and detect vigilance decline in real time through participant’s reaction times during a monotonous task. A lab-based experiment adapting the Sustained Attention to Response Task (SART) is conducted to quantify the effect of monotony on overall performance. Then relevant parameters are used to build a model detecting hypovigilance throughout the experiment. The accuracy of different mathematical models are compared to detect in real-time – minute by minute - the lapses in vigilance during the task. We show that monotonous tasks can lead to an average decline in performance of 45%. Furthermore, vigilance modelling enables to detect vigilance decline through reaction times with an accuracy of 72% and a 29% false alarm rate. Bayesian models are identified as a better model to detect lapses in vigilance as compared to Neural Networks and Generalised Linear Mixed Models. This modelling could be used as a framework to detect vigilance decline of any human performing monotonous tasks.