MULTIPURPOSE MEASUREMENT MODELS FOR ADJUSTMENT BY THE LEAST-SQUARES METHOD

The development of multipurpose measurement models is the precondition for software development for simultaneous adjustment of the large scope and complicated combinations of the measurement results by the least-squares method. Multipurpose measurement models for software can be a helpful tool for processing the final measurement results provided by different measurement methods applying the mentioned software; processing the measurement results of measurement standards comparisons, interlaboratory comparison, and calibration procedures; estimating the additive and multiplicative systematic components of measurement errors and their uncertainty; processing complicated combinations by binding or linking up of the interlaboratory comparison and calibration results in the time; simultaneous processing of the measurement results obtained by various methods e.g. by the method of direct measurements and comparisons; fast-changing the multipurpose measurement models from linear to non-linear type. Processing of the results by software based on the multipurpose measurement model algorithm can help to established a comprehensive measurement traceability network by pooling the single traceability chains.

A weighting method for simultaneous adjustment for confounding and joint exposure-outcome misclassifications

Joint misclassification of exposure and outcome variables can lead to considerable bias in epidemiological studies of causal exposure-outcome effects. In this paper, we present a new maximum likelihood based estimator for marginal causal effects that simultaneously adjusts for confounding and several forms of joint misclassification of the exposure and outcome variables. The proposed method relies on validation data for the construction of weights that account for both sources of bias. The weighting estimator, which is an extension of the outcome misclassification weighting estimator proposed by Gravel and Platt (Weighted estimation for confounded binary outcomes subject to misclassification. Stat Med 2018; 37: 425–436), is applied to reinfarction data. Simulation studies were carried out to study its finite sample properties and compare it with methods that do not account for confounding or misclassification. The new estimator showed favourable large sample properties in the simulations. Further research is needed to study the sensitivity of the proposed method and that of alternatives to violations of their assumptions. The implementation of the estimator is facilitated by a new R function (ipwm) in an existing R package (mecor).

Detection of advanced colorectal neoplasia and relative colonoscopy workloads using quantitative faecal immunochemical tests: an observational study exploring the effects of simultaneous adjustment of both sample number and test positivity threshold

ObjectiveWhen screening for colorectal cancer (CRC) using quantitative faecal immunochemical tests (FIT), test parameters requiring consideration are the faecal haemoglobin concentration (f-Hb) positivity cut-off and the number of stools sampled. This observational study explored variation in f-Hb between samples and the relationship between sensitivity for advanced neoplasia (AN, cancer or advanced adenoma) and colonoscopy workload across a range of independently-adjusted parameter combinations.DesignQuantitative FIT data (OC-Sensor) were accessed from individuals undergoing personalised colonoscopic screening with an offer of 2-sample FIT in the intervening years. We estimated variation in f-Hb between samples in 12 710 completing 2-sample FIT, plus test positivity rates (colonoscopy workload) and sensitivity for AN according to parameter combinations in 4037 instances where FIT was done in the year preceding colonoscopy.ResultsThere was large within-subject variability between samples, with the ratio for the second to the first sample f-Hb ranging up to 18-fold for all cases, and up to 56-fold for AN cases. Sensitivity for AN was greatest at lower f-Hb cut-offs and/or using 2-sample FIT. Colonoscopy workload varied according to how parameters were combined. Using different cut-offs for 1-sample FIT and 2-sample FIT to return similar sensitivity, workload was less with 2-sample FIT when the sensitivity goal exceeded 35%.ConclusionVariation in f-Hb between samples is such that both parameters are crucial determinants of sensitivity and workload; independent adjustment of each should be considered. The 2-sample FIT approach is best for detecting advanced adenomas as well as CRC provided that the colonoscopy workload is feasible.

Attitudes to ageing, biomarkers of ageing and mortality: the Lothian Birth Cohort 1936

ObjectiveTo investigate whether people with more positive attitudes to ageing are biologically younger as defined by leucocyte telomere length, accelerated DNA methylation GrimAge (AgeAccelGrim) and brain-predicted age difference, and whether these biomarkers explain relationships between attitudes to ageing and mortality.MethodsWe used linear regression to examine cross-sectionally attitudes to ageing (measured using the Attitudes to Ageing Questionnaire) and the three biomarkers in 758 adults, mean age 72.5 years, from the Lothian Birth Cohort 1936. We used Cox proportional hazards models to examine longitudinally attitudes to ageing and mortality and the role of the biomarkers.ResultsMore positive attitude to physical change was associated with younger biological age, as measured by AgeAccelGrim and brain-predicted age difference in age-adjusted and sex-adjusted models: for an SD higher score, AgeAccelGrim was lower by -0.73 (95% CI -1.03 to -0.42) of a year, and brain-predicted age difference was lower by -0.87 (1.51 to 0.23) of a year. Both associations were attenuated by adjustment for covariates and not significant after simultaneous adjustment for all covariates and correction for multiple testing. More positive attitudes to physical change were associated with lower mortality: for an SD higher score the age-adjusted and sex-adjusted HR (95% CI) was 0.66 (0.56 to 0.78). Adjustment for AgeAccelGrim or brain-predicted age difference attenuated this association slightly. It remained significant after adjustment for all covariates.ConclusionWe found partial evidence that attitudes to ageing are linked with ageing biomarkers but they accounted for only a little of the association between attitudes and mortality.

Active Chatter Suppression in Turning by Simultaneous Adjustment of Amplitude and Frequency of Spindle Speed Variation

In machining processes, chatter suppression is very important for achieving a high material removal rate, good dimensional accuracy, and surface finish. With the merits of effectiveness and easy implementation, spindle speed variation (SSV) is regarded as a promising approach for chatter suppression. However, there is little research on the selection of SSV parameters for adaptive chatter suppression. Although the effectiveness of adaptively adjusting SSV amplitudes has been recently examined, the simultaneous adjustment of the SSV amplitude and frequency is expected to exhibit stronger adaptability since it achieves greater flexibility. In this paper, an active chatter suppression strategy is presented by simultaneously adjusting the amplitude and frequency of spindle speed variation. The effect of SSV parameters on stability improvement in turning processes including the tool wear is first investigated to demonstrate the necessity of simultaneously adjusting the amplitude and frequency for chatter suppression. Then, the proposed chatter suppression system is introduced, where two SSV parameters are simultaneously adjusted with optimal fractional-order proportional integral differential (FOPID) controllers to keep the chatter indicator close to a target value. Moreover, the FOPID controller is optimally tuned with the JADE algorithm. The effectiveness of the proposed method is verified by comparing simulated results of different SSV parameters adjusting strategies. Finally, machining tests are conducted to validate that the proposed chatter suppression method outperforms the existing SSV method in flexibility and effectiveness.

Do ethnic inequalities in multimorbidity reflect ethnic differences in socioeconomic status? The HELIUS study

Background The burden of multimorbidity is likely higher in ethnic minority populations, as most individual diseases are more prevalent in minority groups. However, information is scarce. We examined ethnic inequalities in multimorbidity, and investigated to what extent they reflect differences in socioeconomic status (SES). Methods We included Healthy Life in an Urban Setting study participants of Dutch (N = 4582), South-Asian Surinamese (N = 3258), African Surinamese (N = 4267), Ghanaian (N = 2282), Turkish (N = 3879) and Moroccan (N = 4094) origin (aged 18–70 years). Educational level, employment status, income situation and multimorbidity were defined based on questionnaires. We described the prevalence and examined age-adjusted ethnic inequalities in multimorbidity with logistic regression analyses. To assess the contribution of SES, we added SES indicators to the age-adjusted model. Results The prevalence of multimorbidity ranged from 27.1 to 53.4% in men and from 38.5 to 69.6% in women. The prevalence of multimorbidity in most ethnic minority groups was comparable to the prevalence among Dutch participants who were 1–3 decades older. After adjustment for SES, the odds of multimorbidity remained significantly higher in ethnic minority groups. For instance, age-adjusted OR for multimorbidity for the Turkish compared to the Dutch changed from 4.43 (3.84–5.13) to 2.34 (1.99–2.75) in men and from 5.35 (4.69–6.10) to 2.94 (2.54–3.41) in women after simultaneous adjustment for all SES indicators. Conclusions We found a significantly higher prevalence of multimorbidity in ethnic minority men and women compared to Dutch, and results pointed to an earlier onset of multimorbidity in ethnic minority groups. These inequalities in multimorbidity were not fully accounted for by differences in SES.