860 research outputs found

    Robust Inference of Trees

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    This paper is concerned with the reliable inference of optimal tree-approximations to the dependency structure of an unknown distribution generating data. The traditional approach to the problem measures the dependency strength between random variables by the index called mutual information. In this paper reliability is achieved by Walley's imprecise Dirichlet model, which generalizes Bayesian learning with Dirichlet priors. Adopting the imprecise Dirichlet model results in posterior interval expectation for mutual information, and in a set of plausible trees consistent with the data. Reliable inference about the actual tree is achieved by focusing on the substructure common to all the plausible trees. We develop an exact algorithm that infers the substructure in time O(m^4), m being the number of random variables. The new algorithm is applied to a set of data sampled from a known distribution. The method is shown to reliably infer edges of the actual tree even when the data are very scarce, unlike the traditional approach. Finally, we provide lower and upper credibility limits for mutual information under the imprecise Dirichlet model. These enable the previous developments to be extended to a full inferential method for trees.Comment: 26 pages, 7 figure

    Effectiveness of delivering integrated COPD care at public healthcare facilities: a cluster randomised trial in Pakistan

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    Background In Pakistan chronic obstructive pulmonary disease (COPD) prevalence is 2.1% in adults aged >40 years. Despite being a health policy focus, integrated COPD care has remained neglected, with wide variation in practice. Aim To assess whether enhanced care at public health facilities resulted in better control of COPD, treatment adherence, and smoking cessation. Design & setting A two-arm cluster randomised controlled trial was undertaken in 30 public health facilities (23 primary and 7 secondary), across three districts of Punjab, between October 2014–December 2016. Both arms had enhanced diagnosis and patient recording processes. Intervention facilities also had clinical care guides; drugs for COPD; patient education flipcharts; associated staff training; and mobile phone follow-up. Method Facilities were randomised in a 1:1 ratio (sealed envelope independent lottery method), and 159 intervention and 154 control patients were recruited. The eligibility criteria were as follows: diagnosed with COPD, aged ≥18 years, and living in the catchment area. The primary outcome was change in BODE (Body mass index, airway Obstruction, Dyspnoea, Exercise capacity) index score from baseline to final follow-up visit. Staff and patients were not blinded. Results Six-month primary outcomes were available for 147/159 (92.5%) intervention and 141/154 (91.6%) control participants (all clusters). The primary outcome results cluster-level analysis were as follows: mean intervention outcome = -1.67 (95% confidence intervals [CI] = -2.18 to -1.16); mean control outcome = -0.66 (95% CI = -1.09 to -0.22); and covariate-adjusted mean intervention–control difference = -0.96 (95% CI = -1.49 to -0.44; P = 0.001). Conclusion The findings of this trial and a separate process evaluation study support the scaling of this integrated COPD care package at primary and secondary level public health facilities in Pakistan and similar settings

    Effectiveness of an integrated diabetes care package at primary healthcare facilities: a cluster randomised trial in Pakistan

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    Background: There were an estimated 7 million people living with diabetes in Pakistan in 2014, and this is predicted to reach 11.4 million by 2030. Aim: To assess if an integrated care package can achieve better control of diabetes. Design & setting: The pragmatic cluster randomised controlled trial (cRCT) was conducted from December 2014–June 2016 at 14 primary healthcare facilities in Sargodha district. Opportunistic screening, diagnostic testing, and patient recording processes were introduced in both the control 'testing, treating, and recording' (TTR) arm, and the intervention 'additional case management' (ACM) arm, which also included a clinical care guide and pictorial flipbook for lifestyle education, associated clinician training, and mobile phone follow-up. Method: Clinics were randomised on a 1:1 basis (sealed envelope lottery method) and 250 patients recruited in the ACM arm and 245 in the TTR-only arm (age ≥25 years and HbA1c >7%). The primary outcome was mean change in HbA1c (%) from baseline to 9-month follow-up. Patients and staff were not blinded. Results: The primary outcome was available for n = 238/250 (95.2%) participants in the ACM arm and n = 219/245 (89.4%) participants in the TTR-only arm (all clusters). Cluster level mean outcome was -2.26 pp (95% confidence intervals [CI] = -2.99 to -1.53) for the ACM arm, and -1.44 pp (95% CI = -2.34 to -0.54) for the TTR-only arm. Cluster level mean ACM–TTR difference (covariate-unadjusted) was -0.82 pp (95% CI = -1.86 to 0.21; P = 0.11). Conclusion: The ACM intervention in public healthcare facilities did not show a statistically significant effect on HbA1c reduction compared to the control (TTR-only) arm. Future evaluation should assess changes after a longer follow-up period, and minimal care enhancement in the comparator (control) arm

    Enhanced hypertension care through private clinics in Pakistan: a cluster randomised trial

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    Background Hypertension in Pakistan affects 33% of people aged ≥45 years, and in urban areas around 70% of basic health care occurs in private facilities. Aim To assess whether enhanced care at urban private clinics resulted in better control of hypertension, cardiovascular disease (CVD) risk factors, and treatment adherence. Design & setting A two-arm cluster randomised controlled trial was conducted at 26 private clinics (in three districts of Punjab) between January 2015–September 2016. Both arms had enhanced screening and diagnosis of hypertension and related conditions, and patient recording processes. Intervention facilities also had a clinical care guide, additional drugs for hypertension, a patient lifestyle education flipchart, associated training, and mobile phone follow-up. Method Clinics were randomised in a 1:1 ratio (sealed envelope lottery method). A total of 574 intervention and 564 control patients in 13 clusters in each arm were recruited (male and female, aged ≥25 years, systolic blood pressure [SBP] >140 mmHg, and/or diastolic blood pressure [DBP] >90 mmHg). The primary outcome was change in SBP from baseline to 9-month follow-up. Staff and patients were not blinded, but outcome assessors were blinded. Results Nine-month primary outcomes were available for 522/574 (90.9%) intervention and 484/564 (85.8%) control participants (all clusters). The unadjusted cluster-level analysis results were as follows: mean intervention outcome was -25.2 mmHg (95% confidence intervals [CI] = -29.9 to -20.6); mean control outcome was -9.4 mmHg (95% CI = 21.2 to 2.2); and mean control–intervention difference was 15.8 (95% CI = 3.6 to 28.0; P = 0.01). Conclusion The findings and separate process evaluation support the scaling of an integrated CVD–hypertension care intervention in urban private clinics in areas lacking public primary care in Pakistan

    Coherent frequentism

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    By representing the range of fair betting odds according to a pair of confidence set estimators, dual probability measures on parameter space called frequentist posteriors secure the coherence of subjective inference without any prior distribution. The closure of the set of expected losses corresponding to the dual frequentist posteriors constrains decisions without arbitrarily forcing optimization under all circumstances. This decision theory reduces to those that maximize expected utility when the pair of frequentist posteriors is induced by an exact or approximate confidence set estimator or when an automatic reduction rule is applied to the pair. In such cases, the resulting frequentist posterior is coherent in the sense that, as a probability distribution of the parameter of interest, it satisfies the axioms of the decision-theoretic and logic-theoretic systems typically cited in support of the Bayesian posterior. Unlike the p-value, the confidence level of an interval hypothesis derived from such a measure is suitable as an estimator of the indicator of hypothesis truth since it converges in sample-space probability to 1 if the hypothesis is true or to 0 otherwise under general conditions.Comment: The confidence-measure theory of inference and decision is explicitly extended to vector parameters of interest. The derivation of upper and lower confidence levels from valid and nonconservative set estimators is formalize
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