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We examined differential item functioning (DIF) of the Center for Epidemiologic Studies Depression Scale (CES-D) items by country and statistically harmonized common cross-national factor scores for the CES-D to aid further cross-national research. Data were from Harmonized Cognitive Assessment Protocol (HCAP) studies in China (N = 9639), England (N = 1262), India (N = 4048), Mexico (N = 1918), South Africa (N = 631), and the United States (N = 3321). Multiple indicators, multiple causes models were estimated to test DIF in the CES-D items by country. DIF items were defined as having an odds ratio (OR) outside the range of 0.75–1.25 in multiple indicators, multiple causes models. We evaluated DIF impact and identified salient DIF by examining whether the difference between DIF-adjusted factor scores and non-DIF–adjusted factor scores exceeded a threshold of 0.30 standard deviation (SD) units. Confirmatory factor analysis was used to create DIF-adjusted, cross-nationally harmonized CES-D factor scores. Controlling for underlying depressive symptoms, HCAP participants in India had higher odds of reporting being not hopeful about future (OR = 1.38, 95% confidence interval [CI]: 1.34–1.42), not enjoying life (OR = 1.43, 95% CI: 1.38–1.48), and being unhappy (OR = 1.29, 95% CI: 1.25–1.34), compared to HCAP participants in the United States. These identified DIF items artificially increased mean harmonized CES-D factor scores by 0.48 SD units in the India HCAP, with over 50% of the factor scores increased by over 0.30 SD units, indicating salient DIF in the India HCAP. Our findings demonstrate cross-national heterogeneity in the expression of depressive symptoms. We provide DIF-adjusted CES-D factor scores to improve the quality of cross-national comparisons in aging research. •Inconsistent CES-D items challenge cross-national comparisons of depression.•We detected items with salient DIF in LASI-DAD, relative to other HCAP studies.•Items with DIF increased mean CES-D factor scores by 0.48 SD units in LASI-DAD.•DIF items in LASI-DAD should be adjusted for further cross-national comparisons.

INTRODUCTION Harmonizing cognitive measures across population‐based studies facilitates direct comparisons of cognitive decline despite differing study protocols. METHODS Cognitive performance data from 2012–2022 were harmonized across the Health and Retirement Study (HRS) and National Health and Aging Trends Study (NHATS). We compared baseline harmonized scores stratified by demographics and examined demographic and health risk factor associations with cognitive change using multi‐level generalized linear models, contrasting results with those from a sum‐of‐word‐recall measure. RESULTS Cross‐sectionally, lower harmonized scores were associated with older age and less education. Longitudinally, greater cognitive decline measured by changes in harmonized scores correlated with older age, less education, underweight body mass index, low physical activity, hypertension, stroke, and diabetes. Associations were stronger for harmonized scores than for sum of word recall alone. DISCUSSION Harmonized scores effectively capture cognitive performance and decline, demonstrating stronger relationships with demographic and health factors than word recall scores alone. Highlights Statistical harmonization is a valuable tool for undertaking comparative analysis when data collection protocols differ. We derived a harmonized general cognitive performance factor score for the Health and Retirement Study (HRS) and National Health and Aging Trends Study (NHATS), two of the largest, nationally representative longitudinal samples of the middle‐aged and older adult population in the United States. The factor score showed patterns of change across exposure groups consistent with prior literature, and it outperformed a simple sum score of immediate and delayed word recall tests.

Background Data harmonization is a powerful method to equilibrate items in measures that evaluate the same underlying construct. There are multiple measures to evaluate dementia related behavioral symptoms. Pre-statistical harmonization of behavioral instruments in dementia research is the first step to develop a statistical crosswalk between measures. Studies that conduct pre-statistical harmonization of behavioral instruments rarely document their methods in a structured, reproducible manner. This is a crucial step which entails careful review, documentation and scrutiny of source data to ensure sufficient comparability between items prior to data pooling. Here, we document the pre-statistical harmonization of items measuring behavioral and psychological symptoms among people with dementia. We provide a box of recommended procedure for future studies. Methods We identified behavioral instruments that are used in clinical practice, a national survey, and randomized trials of dementia care interventions. We rigorously reviewed question content and scoring procedures to establish sufficient comparability across items as well as item quality prior to data pooling. Additionally, we standardized coding to Stata-readable format, which allowed us to automate approaches to identify potential cross-study differences in items and low-quality items. To ensure reasonable model fit for statistical co-calibration, we estimated two-parameter logistic Item Response Theory models within each of the eight studies. Results We identified 59 items from 11 behavioral instruments across the eight datasets. We found considerable cross-study heterogeneity in administration and coding procedures for items that measure the same attribute. Discrepancies existed in terms of directionality and quantification of behavioral symptoms for even seemingly comparable items. We resolved item response heterogeneity, missingness and skewness, conditional dependency prior to estimation of item response theory models for statistical co-calibration. We used several rigorous data transformation procedures to address these issues, including re-coding and truncation. Conclusions This study highlights the importance of each aspect involved in the pre-statistical harmonization process of behavioral instruments. We provide guidelines and recommendations for how future research may detect and account for similar issues in pooling behavioral and related instruments.

Data harmonization is a powerful method to equilibrate items in measures that evaluate the same underlying construct. There are multiple measures to evaluate dementia related behavioral symptoms. Pre-statistical harmonization of behavioral instruments in dementia research is the first step to develop a statistical crosswalk between measures. Studies that conduct pre-statistical harmonization of behavioral instruments rarely document their methods in a structured, reproducible manner. This is a crucial step which entails careful review, documentation and scrutiny of source data to ensure sufficient comparability between items prior to data pooling. Here, we document the pre-statistical harmonization of items measuring behavioral and psychological symptoms among people with dementia. We provide a box of recommended procedure for future studies. We identified behavioral instruments that are used in clinical practice, a national survey, and randomized trials of dementia care interventions. We rigorously reviewed question content and scoring procedures to establish sufficient comparability across items as well as item quality prior to data pooling. Additionally, we standardized coding to Stata-readable format, which allowed us to automate approaches to identify potential cross-study differences in items and low-quality items. To ensure reasonable model fit for statistical co-calibration, we estimated two-parameter logistic Item Response Theory models within each of the eight studies. We identified 59 items from 11 behavioral instruments across the eight datasets. We found considerable cross-study heterogeneity in administration and coding procedures for items that measure the same attribute. Discrepancies existed in terms of directionality and quantification of behavioral symptoms for even seemingly comparable items. We resolved item response heterogeneity, missingness and skewness, conditional dependency prior to estimation of item response theory models for statistical co-calibration. We used several rigorous data transformation procedures to address these issues, including re-coding and truncation. This study highlights the importance of each aspect involved in the pre-statistical harmonization process of behavioral instruments. We provide guidelines and recommendations for how future research may detect and account for similar issues in pooling behavioral and related instruments.

Introduction Efforts to harmonize measures of everyday function and dementia‐related behaviors are needed to synthesize across studies in dementia research. There have been some psychometric attempts to harmonize everyday function for secondary analysis, but far less for dementia‐related behaviors. Methods Statistical co‐calibration was performed to generate factor scores representing everyday function and dementia‐related behaviors for participants with dementia. We evaluated convergent criterion validity of factor scores and mapped the scores onto established clinical instruments. Results Factor analyses of included items fit well to available data. Harmonized factors showed expected associations with the Global Clinical Dementia Rating (CDR) score, with greater impairment (higher Global CDR score) corresponding to higher (more severe) levels on factor scores. Discussion We used large, well‐characterized samples to derive harmonized factors representing everyday functions and dementia‐related behaviors. These harmonized factors can be used to tackle questions about dementia phenotypes which require either large samples or unique subpopulations.

The process of European statistical harmonisation implies continuous harmonisation of statistical methodology, business and IT processes and IT solutions. It is based on the generic and standardised information concepts and methods, a common legal framework and terminology as well as on the modular and interoperable IT infrastructure. In the context of this article, statistical harmonisation is related to the harmonisation of the Croatian system of official statistics with the European Statistical System, coordinated by the European Commission via Eurostat. The Croatian Bureau of Statistics is the main national carrier and coordinator of the official statistics and the main representative of the Croatian statistical system before the European and international authorities responsible for statistics. As its part, the Croatian statistical system is largely dependent on the European Statistical System. In this paper, critical discourse analysis was used to analyse Eurostat’s control mechanisms over the national statistical authority, which enable and legitimise the interaction between these two participants in the process of statistical harmonisation. To assess the extent to which the ideological discourses of the European statistical harmonisation structured the national statistical institution, eighteen semi-structured interviews were conducted with employees of the Croatian Bureau of Statistics. A sample of intensity was used. It included informants that are familiar with the research topic as they frequently communicate and collaborate with colleagues from Eurostat on the harmonisation of statistical and information systems. Based on the results, it was concluded that the negative connotation of Eurostat’s authority, acquired prior to Croatia’s accession to the European Union, has changed in the discourse of the Croatian Bureau of Statistics after the accession, with Eurostat gaining an authority of a role model. However, the Croatian Bureau of Statistics has yet to evolve from a passive follower of Eurostat’s requests to an equal member of the European Statistical System with an active role in the creation of statistical harmonisation processes.

More than ever, data drives decisions in organizations--and we have more data, and more ways to analyze it, than ever. Yet strategic initiatives continue to fail as often as they did when computers ran on punch cards. Economist and research scientist Alec Levenson says we need a new approach. The problem, Levenson says, is that the business people who devise the strategies and the human resources people who get employees to implement them use completely different analytics. Business analytics can determine if operational priorities aren't being achieved but can't explain why. HR analytics reveal potentially helpful policy and process improvements but can't identify which would have the greatest strategic impact. This book shows how to use an integrated approach to bring these two pieces together. Levenson presents a thorough and realistic treatment of the reasons for and challenges of taking an integrated approach. He provides details on the different parts of both enterprise and human capital analytics that have to be conducted for integration to be successful and includes specific questions to ask, along with examples of applying integrated analytics to address particular organizational challenges.

Proces europske statističke harmonizacije podrazumijeva kontinuirano usklađivanje statističke metodologije, poslovnih i informacijskih procesa te informatičkih rješenja, a temelji se na generičkim i standardiziranim informacijskim konceptima i metodama, zajedničkom pravnom okviru i terminologiji te na modularnoj i interoperabilnoj informatičkoj infrastrukturi. U kontekstu ovog članka, statistička se harmonizacija odnosi na usklađivanje hrvatskog sustava službene statistike s Europskim statističkim sustavom, čiji je koordinator Europska komisija, odnosno Eurostat. Državni zavod za statistiku Republike Hrvatske glavni je nacionalni nositelj službene statistike i koordinator procesa statističke harmonizacije te glavni predstavnik nacionalnoga statističkog sustava pred europskim i međunarodnim tijelima nadležnima za statistiku. Kao njegov dio, hrvatski statistički sustav umnogome ovisi o Europskome statističkom sustavu. U ovom se radu kritičkom analizom diskursa razmatraju nadzorni mehanizmi Eurostata nad nacionalnim statističkim tijelom, koji omogućuju i legitimiraju interakciju tih dvaju aktera u procesu statističke harmonizacije. Da bi se ustanovilo u kojoj mjeri ideološki diskursi europske statističke harmonizacije strukturiraju nacionalnu statističku instituciju, provedeno je osamnaest polustrukturiranih intervjua sa zaposlenicima Državnog zavoda za statistiku. Odabran je uzorak intenziteta, odnosno kazivači koji poznaju problematiku istraživanja zbog suradnje s kolegama iz Eurostata na procesima i projektima usklađivanja statističkih ili informacijskih sustava. Temeljem dobivenih rezultata zaključuje se da se u diskursu nacionalnoga statističkog tijela mijenja negativno konotirani autoritet Eurostata, koji datira još iz vremena prije članstva Hrvatske u Europskoj uniji, te da Eurostat stječe autoritet uzora. No, Državni zavod za statistiku tek se treba razviti od pasivnog Eurostatova poslušnika do ravnopravnog člana Europskoga statističkog sustava s ulogom aktivnog kreatora procesa statističke harmonizacije.

With the proliferation of multi-site neuroimaging studies, there is a greater need for handling non-biological variance introduced by differences in MRI scanners and acquisition protocols. Such unwanted sources of variation, which we refer to as “scanner effects”, can hinder the detection of imaging features associated with clinical covariates of interest and cause spurious findings. In this paper, we investigate scanner effects in two large multi-site studies on cortical thickness measurements across a total of 11 scanners. We propose a set of tools for visualizing and identifying scanner effects that are generalizable to other modalities. We then propose to use ComBat, a technique adopted from the genomics literature and recently applied to diffusion tensor imaging data, to combine and harmonize cortical thickness values across scanners. We show that ComBat removes unwanted sources of scan variability while simultaneously increasing the power and reproducibility of subsequent statistical analyses. We also show that ComBat is useful for combining imaging data with the goal of studying life-span trajectories in the brain. •Cortical thickness (CT) measurements are highly scanner specific.•Identifying scanner effects is crucial for inference and biomarker development.•We propose to use ComBat to harmonize cortical thickness values across scanners.

The parametric catalogue of Italian earthquakes CPTI15 (Catalogo Parametrico dei Terremoti Italiani) represents the latest of a 45-years-long tradition of earthquake catalogues for Italy, and a significant innovation with respect to its predecessors. CPTI15 combines all known information on significant Italian earthquakes of the period 1000–2017, balancing instrumental and macroseismic data. Although the compilation criteria are the same as in the previous CPTI11 version, released in 2012, the catalogue has been revised as concerns: the time coverage, extended to 2017; the associated macroseismic data, improved in quantity and quality; the considered instrumental data, new and/or updated; the energy thresholds, lowered to maximum or epicentral intensity 5 or magnitude 4.0 (instead of 5–6 and 4.5, respectively); the determination of parameters from macroseismic data, based on a new calibration; the instrumental magnitudes, resulting from new sets of data and new conversion relationships to Mw. The catalogue considers and harmonizes data of different types and origins, both macroseismic and instrumental. For all earthquakes, the magnitude is given in terms of true or proxy moment magnitude (Mw), with the related uncertainty. The compilation procedure rigorously implements data and methods published in peer-reviewed journals. All data and methods are clearly indicated in the catalogue, in order to guarantee the maximum transparency of the compilation procedures. As compared to previous CPTI releases, the final CPTI15 catalogue shows a frequency–magnitude distribution coherent with current Italian instrumental catalogues, making it suitable for statistical analysis of the time-space property of the Italian seismicity.