A Mixed Model for Analyzing Measurement Errors for Dichotomous Variables

Author(s):  
Jeroen Pannekoek
2021 ◽  
Author(s):  
Maude Wagner ◽  
Francine Grodstein ◽  
Karen Leffondre ◽  
Cécilia Samieri ◽  
Cécile Proust-Lima

Abstract Background: Long-term behavioral and health risk factors constitute a primary focus of research on the etiology of chronic diseases. Yet, identifying critical time-windows during which risk factors have the strongest impact on disease risk is challenging. To assess the trajectory of association of an exposure history with an outcome, the weighted cumulative exposure index (WCIE) has been proposed, with weights reflecting the relative importance of exposures at different times. However, WCIE is restricted to a complete observed error-free exposure whereas exposures are often measured with intermittent missingness and error. Moreover, it rarely explores exposure history that is very distant from the outcome as usually sought in life-course epidemiology.Methods: We extend the WCIE methodology to (i) exposures that are intermittently measured with error, and (ii) contexts where the exposure time-window precedes the outcome time-window using a landmark approach. First, the individual exposure history up to the landmark time is estimated using a mixed model that handles missing data and error in exposure measurement, and the predicted complete error-free exposure history is derived. Then the WCIE methodology is applied to assess the trajectory of association between the predicted exposure history and the health outcome collected after the landmark time. In our context, the health outcome is a longitudinal marker analyzed using a mixed model.Results: A simulation study first demonstrates the correct inference obtained with this approach. Then, applied to the Nurses’ Health Study (19,415 women) to investigate the association between body mass index history (collected from midlife) and subsequent cognitive decline (evaluated after age 70), the method identified two major critical windows of association: long before the first cognitive evaluation (roughly 24 to 12 years), higher levels of BMI were associated with poorer cognition. In contrast, adjusted for the whole history, higher levels of BMI became associated with better cognition in the last years prior to the first cognitive interview, thus reflecting reverse causation (changes in exposure due to underlying disease).Conclusions: This approach, easy to implement, provides a flexible tool for studying complex dynamic relationships and identifying critical time windows while accounting for exposure measurement errors.


Author(s):  
Rauf Ahmad ◽  
Silvelyn Zwanzig

The objective of this study is to evaluate the total least squares (TLS) estimator for the linear mixed model when the design matrix is subject to measurement errors, with special focus on models for longitudinal or repeated-measures data. We consider measurement errors only in the design matrix concerning the fixed part of the model and estimate its corresponding parameter vector under the TLS set up. After treating two variants of the general case, the random coefficient model is discussed as a special case. We evaluate conditions, on the design matrices as well as on variance component parameters, under which a reasonable TLS estimator can be expected in such models. Analysis of a real data example is also provided.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Maude Wagner ◽  
Francine Grodstein ◽  
Karen Leffondre ◽  
Cécilia Samieri ◽  
Cécile Proust-Lima

Abstract Background Long-term behavioral and health risk factors constitute a primary focus of research on the etiology of chronic diseases. Yet, identifying critical time-windows during which risk factors have the strongest impact on disease risk is challenging. To assess the trajectory of association of an exposure history with an outcome, the weighted cumulative exposure index (WCIE) has been proposed, with weights reflecting the relative importance of exposures at different times. However, WCIE is restricted to a complete observed error-free exposure whereas exposures are often measured with intermittent missingness and error. Moreover, it rarely explores exposure history that is very distant from the outcome as usually sought in life-course epidemiology. Methods We extend the WCIE methodology to (i) exposures that are intermittently measured with error, and (ii) contexts where the exposure time-window precedes the outcome time-window using a landmark approach. First, the individual exposure history up to the landmark time is estimated using a mixed model that handles missing data and error in exposure measurement, and the predicted complete error-free exposure history is derived. Then the WCIE methodology is applied to assess the trajectory of association between the predicted exposure history and the health outcome collected after the landmark time. In our context, the health outcome is a longitudinal marker analyzed using a mixed model. Results A simulation study first demonstrates the correct inference obtained with this approach. Then, applied to the Nurses’ Health Study (19,415 women) to investigate the association between body mass index history (collected from midlife) and subsequent cognitive decline (evaluated after age 70), the method identified two major critical windows of association: long before the first cognitive evaluation (roughly 24 to 12 years), higher levels of BMI were associated with poorer cognition. In contrast, adjusted for the whole history, higher levels of BMI became associated with better cognition in the last years prior to the first cognitive interview, thus reflecting reverse causation (changes in exposure due to underlying disease). Conclusions This approach, easy to implement, provides a flexible tool for studying complex dynamic relationships and identifying critical time windows while accounting for exposure measurement errors.


Psychometrika ◽  
2021 ◽  
Author(s):  
Domingo Morales ◽  
Joscha Krause ◽  
Jan Pablo Burgard

AbstractMajor depression is a severe mental disorder that is associated with strongly increased mortality. The quantification of its prevalence on regional levels represents an important indicator for public health reporting. In addition to that, it marks a crucial basis for further explorative studies regarding environmental determinants of the condition. However, assessing the distribution of major depression in the population is challenging. The topic is highly sensitive, and national statistical institutions rarely have administrative records on this matter. Published prevalence figures as well as available auxiliary data are typically derived from survey estimates. These are often subject to high uncertainty due to large sampling variances and do not allow for sound regional analysis. We propose a new area-level Poisson mixed model that accounts for measurement errors in auxiliary data to close this gap. We derive the empirical best predictor under the model and present a parametric bootstrap estimator for the mean squared error. A method of moments algorithm for consistent model parameter estimation is developed. Simulation experiments are conducted to show the effectiveness of the approach. The methodology is applied to estimate the major depression prevalence in Germany on regional levels crossed by sex and age groups.


Author(s):  
Danan Gu

Successful aging has extended from the biomedical-oriented model to the biomedi-cal-and-psychosocial mixed model. However, few studies have investigated the subtypes of the joint classification between subjective (psychosocial-oriented) (SSA) and objective (biomedi-cal-oriented) (OSA) measures to identify and distinguish different risk groups. This study aims to examine how concordance and discordance between SSA and OSA are associated with sub-sequent mortality based on five waves of a nationwide longitudinal survey in China from 2000 to 2011 with 30,948 sampled persons aged 65 and older. SSA was measured by absence of poor life satisfaction, poor self-rated health, and psychological distress, while OSA was measured by absence of disability, cognitive impairment, and chronic diseases. We then defined a variable with four subtypes of concordance and discordance from these two dichotomous variables: Type I (not-OSA & not-SSA), Type II (not-OSA & SSA), Type III (OSA & not-SSA) and Type IV (OSA & SSA). Types I and IV are concordance types, while Types II and III are discordance types. The results showed that a negative association between Type IV (SSA & OSA) and risk of mortality was universal over age groups and sexes. Compared to Type I (not-SSA & not-OSA), Type IV (SSA & OSA) has a 25–71% lower risk of mortality, depending on age group and sex, after controlling for a rich set of confounders. Concordance and discordance between OSA and SSA provide added power in predicting subsequent mortality. Public health programs should target those more vulnerable subtypes to promote successful aging.


Author(s):  
W.J. de Ruijter ◽  
Sharma Renu

Established methods for measurement of lattice spacings and angles of crystalline materials include x-ray diffraction, microdiffraction and HREM imaging. Structural information from HREM images is normally obtained off-line with the traveling table microscope or by the optical diffractogram technique. We present a new method for precise measurement of lattice vectors from HREM images using an on-line computer connected to the electron microscope. It has already been established that an image of crystalline material can be represented by a finite number of sinusoids. The amplitude and the phase of these sinusoids are affected by the microscope transfer characteristics, which are strongly influenced by the settings of defocus, astigmatism and beam alignment. However, the frequency of each sinusoid is solely a function of overall magnification and periodicities present in the specimen. After proper calibration of the overall magnification, lattice vectors can be measured unambiguously from HREM images.Measurement of lattice vectors is a statistical parameter estimation problem which is similar to amplitude, phase and frequency estimation of sinusoids in 1-dimensional signals as encountered, for example, in radar, sonar and telecommunications. It is important to properly model the observations, the systematic errors and the non-systematic errors. The observations are modelled as a sum of (2-dimensional) sinusoids. In the present study the components of the frequency vector of the sinusoids are the only parameters of interest. Non-systematic errors in recorded electron images are described as white Gaussian noise. The most important systematic error is geometric distortion. Lattice vectors are measured using a two step procedure. First a coarse search is obtained using a Fast Fourier Transform on an image section of interest. Prior to Fourier transformation the image section is multiplied with a window, which gradually falls off to zero at the edges. The user indicates interactively the periodicities of interest by selecting spots in the digital diffractogram. A fine search for each selected frequency is implemented using a bilinear interpolation, which is dependent on the window function. It is possible to refine the estimation even further using a non-linear least squares estimation. The first two steps provide the proper starting values for the numerical minimization (e.g. Gauss-Newton). This third step increases the precision with 30% to the highest theoretically attainable (Cramer and Rao Lower Bound). In the present studies we use a Gatan 622 TV camera attached to the JEM 4000EX electron microscope. Image analysis is implemented on a Micro VAX II computer equipped with a powerful array processor and real time image processing hardware. The typical precision, as defined by the standard deviation of the distribution of measurement errors, is found to be <0.003Å measured on single crystal silicon and <0.02Å measured on small (10-30Å) specimen areas. These values are ×10 times larger than predicted by theory. Furthermore, the measured precision is observed to be independent on signal-to-noise ratio (determined by the number of averaged TV frames). Obviously, the precision is restricted by geometric distortion mainly caused by the TV camera. For this reason, we are replacing the Gatan 622 TV camera with a modern high-grade CCD-based camera system. Such a system not only has negligible geometric distortion, but also high dynamic range (>10,000) and high resolution (1024x1024 pixels). The geometric distortion of the projector lenses can be measured, and corrected through re-sampling of the digitized image.


2020 ◽  
Vol 29 (3) ◽  
pp. 391-403
Author(s):  
Dania Rishiq ◽  
Ashley Harkrider ◽  
Cary Springer ◽  
Mark Hedrick

Purpose The main purpose of this study was to evaluate aging effects on the predominantly subcortical (brainstem) encoding of the second-formant frequency transition, an essential acoustic cue for perceiving place of articulation. Method Synthetic consonant–vowel syllables varying in second-formant onset frequency (i.e., /ba/, /da/, and /ga/ stimuli) were used to elicit speech-evoked auditory brainstem responses (speech-ABRs) in 16 young adults ( M age = 21 years) and 11 older adults ( M age = 59 years). Repeated-measures mixed-model analyses of variance were performed on the latencies and amplitudes of the speech-ABR peaks. Fixed factors were phoneme (repeated measures on three levels: /b/ vs. /d/ vs. /g/) and age (two levels: young vs. older). Results Speech-ABR differences were observed between the two groups (young vs. older adults). Specifically, older listeners showed generalized amplitude reductions for onset and major peaks. Significant Phoneme × Group interactions were not observed. Conclusions Results showed aging effects in speech-ABR amplitudes that may reflect diminished subcortical encoding of consonants in older listeners. These aging effects were not phoneme dependent as observed using the statistical methods of this study.


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