Exposure Measurement Error Bias Amplification

Consider an observational study of the association between a continuous exposure and outcome, where the exposure variable of primary interest suffers classical measurement error (i.e., the measured exposures are distributed around the true exposure with independent error). In the absence of exposure measurement error, it is widely recognized that one should control for confounders of the association of interest to obtain an unbiased estimate of the effect of that exposure on the outcome of interest. However, we show that, in the presence of classical exposure measurement error, the net bias in an estimate of the association of interest may increase upon adjustment for confounders. We offer an analytical expression for the change in net bias in an estimate of the association of interest upon adjustment for a confounder in the presence of classical exposure measurement error, and illustrate this problem using simulations.

Analisis Faktor yang Mempengaruhi Pertumbuhan Ekonomi Di Kabupaten Mojokerto

Pertumbuhan ekonomi merupakan laju pertumbuhan yang terbentuk dari berbagai macam sektor ekonomi yang tidak langsung menggambarkan tingkat perubahan ekonomi yang terjadi. Analisa ini ditujukan untuk mencari faktor-faktor yang mempengaruhi pertumbuhan ekonomi di Kabupaten Mojokerto yang nantinya akan diketahui signifikan tidaknya faktor tersebut terhadap pertumbuhan ekonomi di Kabupaten Mojokerto. Penelitian ini bertujuan untuk mengetahui variabel apa yang memiliki pengaruh terbesar terhadap pertumbuhan ekonomi di Kabupaten Mojokerto. Variabel yang diuji adalah investasi, jumlah industri, kurs valuta asing dan ekspor. Penelitian ini menggunakan data sekunder yang diambil dari Badan Pusat Statistik Kabupaten Mojokerto, dengan time series data Tahun 2002-2018. Model analisis yang digunakan adalah analisis regresi linier berganda dengan asumsi BLUE (Best Linier Unbiased Estimate) dengan tujuan untuk mengetahui koefisiensi pada persamaan tersebut benar (tidak bias). Berdasarkan hasil uji regresi linier berganda yang dilakukan, diperoleh hasil bahwa variabel jumlah industri sangat berpengaruh terhadap pertumbuhan ekonomi di Kabupaten Mojokerto, sedangkan ketiga faktor lainnya yakni investasi, kurs dan ekspor tidak berpengaruh secara signifikan terhadap pertumbuhan ekonomi di Kabupaten Mojokerto.

Using Mixed Methods to Explore Variations in Impact Within RCTs: The Case of Project COMPASS

Randomized controlled trials (RCTs) in education are common as the design allows for an unbiased estimate of the overall impact of a program. As more RCTs are completed, researchers are also noting that an overall average impact may mask substantial variation across sites or groups of individuals. Mixed methods can provide insight and help in unpacking some of the reasons for these variations in impact. This article contributes to the field of mixed methods research by integrating mixed methods into a recently developed conceptual framework for understanding variations in impact. We model the use of this approach within the context of an RCT for online courses that found differences in impact across courses.

Domain studies with imperfect frame in large population

Existence of the frame is pre-requisite for any sample survey or census of a large population. Frames are quite often imperfect due to dynamic nature of sampling units. Frames become incomplete by the time actual survey and enumeration starts which affects the statistical results desired for the target population. In present study imperfection in the frame of large population arising due to qualitative change of units from one class to other have been considered. We have considered incomplete frame assuming the nature of units following dynamic change from class one to other follow a probability distribution function. Suitable estimator for proportion of units belonging to a particular domain and unbiased estimate of target population for a class have been proposed along with its estimate of variance. The estimates are evolved so as to eliminate error caused due to deviation of sampled population from target population. The paper deals with interesting problem arising in survey sampling and is useful in practice.

Incorporation of Evidence Based Guidelines on Bleeding Risk Assessment Prior to Surgery into Practice: Real Time Experience

Background: Despite guidelines recommending no-need for coagulation testing prior to surgeries when challenging history of bleeding is negative, yet surgeons still overuse it in this part of the world. We aim to measure unbiased estimate of hemostatic outcomes in ENT surgeries and assess the surgeons’ behavior of pre-operative coagulation testing. Methods: All patients who underwent ENT surgeries during the period from July 2017 to January 2018 were enrolled. The primary outcome was post-operative bleeding. Surgeons were asked about their decision on history alone or doing coagulation testing and their reason. 2 Results: 730 patients were recruited; 372 were interviewed for a challenging bleeding history alone; group1 and 358 had pre-operative coagulation testing; group2. Coagulation testing was repeated twice or more in 55% of patients and more than half of them had coagulation factor and VWF assays. Most surgeons were doing the coagulation testing because of habitual practice. Conclusion: Almost half of local surgeons consider coagulation testing as standard practice to evaluate bleeding risk prior to surgical procedures. This has resulted in unnecessary delays in surgeries, parents/patients anxiety and additional total cost. We recommend awareness campaigns for surgeons and involvement of surgical societies to adhere to guidelines of detailed hemostatic history.

Comparing Patient- and Clinician-Administered Near Point of Convergence After Concussion

Objective: (1) To compare patient- and clinician-administered measurements of near point of convergence (NPC) distance including the percentage of patients exceeding clinical cutoffs among concussed adolescents and (2) to assess the reliability of patient- and clinician-measured NPC distances. Methods: A total of 762 patients (mean = 15.51, SD = 3.09 y) within 30 days of concussion participated. The NPC distance was measured consecutively with the patient and clinician controlling the fixation target. The differences between patient (PT) and clinician (CLIN) measurements and cases exceeding cutoffs (ie, ≥5 cm) were examined with a series of t tests and chi-square tests, respectively. Intraclass correlation coefficients and unbiased estimate of reliability were performed. Results: The NPC measurements were similar, t(761) = −.26, P = .79, between the PT (mean = 3.52, SD = 3.77 cm) and CLIN (mean = 3.54, SD = 3.97 cm) conditions. The number of measurements that exceeded cutoffs was similar among the PT (2.5%; 19/762) and CLIN conditions (3%; 23/762) (P = .10), and the number of measurements classified as abnormal/invalid was also similar among the PT (2.5%; 19/762) and CLIN conditions (3%; 23/762) (P = .10). There was excellent reliability between the methods (intraclass correlation coefficients = .85, unbiased estimate of reliability = .92). Conclusion: The findings support the application of this assessment in clinical settings where the clinician may not have direct contact with their patient and rely on the patient (eg, telehealth).

Approximate guaranteed estimates for matrices in linear regression problems with a small parameter

The problem of finding linear unbiased estimates of the linear operator of unknown matrices — components of the observations vector, is investigated. It is assumed that the observation vector additively depends on a random vector with zero expected value, and the unknown correlation matrix belongs to a known bounded set. For the introduced class of linear estimates, necessary and sufficient conditions for the existence of solutions of operator equations that determine the unknown parameters of the vector estimate, are proved. The form of the guaranteed mean square error of the estimate is introduced on the sets of constraints of the problem parameters. The influence on the linear unbiased estimate of small perturbations of known rectangular matrices, which are the composites of the observations vector components, is also investigated. The analytical form is given through the parameters of the perturbed set of singularities for the introduced special operators that depend on a small parameter, which determine the corresponding operator equations, as well as their approximate solutions, in the first approximation of the small parameter method. A test example of solving the problem of finding a linear unbiased estimate under the condition of perturbation of both linearly independent and linearly dependent known observation matrices is presented.

Demonstrating the Tapered Gridded Estimator (TGE) for the Cosmological HI 21-cm Power Spectrum using 150 MHz GMRT observations

We apply the Tapered Gridded Estimator (TGE) for estimating the cosmological 21-cm power spectrum from 150 MHz GMRT observations which corresponds to the neutral hydrogen (HI) at redshift z = 8.28. Here TGE is used to measure the Multi-frequency Angular Power Spectrum (MAPS) Cℓ(Δν) first, from which we estimate the 21-cm power spectrum P(k⊥, k∥). The data here are much too small for a detection, and the aim is to demonstrate the capabilities of the estimator. We find that the estimated power spectrum is consistent with the expected foreground and noise behaviour. This demonstrates that this estimator correctly estimates the noise bias and subtracts this out to yield an unbiased estimate of the power spectrum. More than $47\%$ of the frequency channels had to be discarded from the data owing to radio-frequency interference, however the estimated power spectrum does not show any artifacts due to missing channels. Finally, we show that it is possible to suppress the foreground contribution by tapering the sky response at large angular separations from the phase center. We combine the k modes within a rectangular region in the ‘EoR window’ to obtain the spherically binned averaged dimensionless power spectra Δ2(k) along with the statistical error σ associated with the measured Δ2(k). The lowest k-bin yields Δ2(k) = (61.47)2 K2 at k = 1.59 Mpc−1, with σ = (27.40)2 K2. We obtain a 2 σ upper limit of (72.66)2 K2 on the mean squared HI 21-cm brightness temperature fluctuations at k = 1.59 Mpc−1.

A Machine Learning approach for assessing drug development risk

ABSTRACTCharacterizing drug development risk – the probability that a drug will eventually receive regulatory approval – has been notoriously hard given the complexities of drug biology and clinical trials. This often leads to an inefficient allocation of resources, and an overall reduction in R&D productivity. We propose a Machine Learning (ML) approach that provides a more accurate and unbiased estimate of drug development risk than traditional models.

Determination of miscalibrated polarization angles from observed cosmic microwave background and foreground EB power spectra: Application to partial-sky observation

We study a strategy to determine miscalibrated polarization angles of cosmic microwave background (CMB) experiments using the observed $EB$ polarization power spectra of CMB and Galactic foreground emission. We apply the methodology of Y. Minami et al. (Prog. Theor. Exp. Phys. 2019, 083E02, 2019), developed for full-sky observations to ground-based experiments such as Simons Observatory. We take into account the $E$-to-$B$ leakage and $\ell$-to-$\ell$ covariance due to partial sky coverage using the public code NaMaster. We show that our method yields an unbiased estimate of miscalibrated angles. Our method also enables simultaneous determination of miscalibrated angles and the intrinsic $EB$ power spectrum of polarized dust emission when the latter is proportional to $\sqrt{C_\ell^{EE}C_\ell^{BB}}$ and $C_\ell^{BB}$ is proportional to $C_\ell^{EE}$.