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This paper proposes comparative research on support provided outside the household by older adults in Europe. In studying social support, the network perspective is widely used, investigating, in particular, the ego-centered support networks of individuals. The analysis is based on data from Wave 7 of the Survey of Health Ageing and Retirement in Europe (SHARE). It examines the characteristics of ego-support networks of individuals aged 65 and over in 12 European countries, which are grouped into a novel welfare regime typology. Through Multiple Correspondence Analysis, we jointly looked into the categorical variables describing the recipients (alters) of the support provided by older adults and the welfare regime classification. As a main result, countries grouped in “High degree of familialism by default” category specialized in supporting family-related alters, particularly with childcare or personal care. In contrast, the elders in countries belonging to “High degree of de-familialisation” typology provided a more varied but less demanding support, to non-relatives alters and less oriented to care. The analyses show that the SHARE provides a solid opportunity to face the topic.

Providing support outside the household can be considered an actual sign of an active social life for the elderly. Adopting an ego–network perspective, we study support Italian elders provide to kin or non–kin. More specifically, using Italian survey data, we build the ego–centered networks of social contacts elders entertain and the ego–networks of support elders provide to other non–cohabitant kin or non–kin. Since ego–network data are inherently multilevel, we use Bayesian multilevel models to analyze variation in support ties, controlling for the characteristics of elders and their contacts. This modeling strategy enables dealing with sparseness and alter–alter overlap in the ego support network data and to disentangle the effects related to the ego (the elder), the dyad ego–alter, the kind of support provided, as well as social contacts and contextual variables. The results suggest that the elderly in Italy who provide support outside their household — compared to all elders in the sample — are younger, healthier, more educated, and embedded in a more diversified ego–network of social contacts. The latter also conveys both the type and the recipient of the support, with the elderly who entertain few relationships with kin being more prone to provide aid to non–kin. Further, a “peer homophily” effect in directing elder support to a non–kin is also found.

The policies for containing the spread of the SARS-CoV2 virus include a number of measures aimed at reducing physical contacts. In this paper, we explore the potential impact of such containment measures on social relations of both young adults and the elderly in Italy. We propose two ego-centered network definitions accounting for physical distance in light of the COVID-19 containment measures: the easy-to-reach network, that represents an accessible source of support that can be activate in case of new lockdown; the accustomed-to-reach network, which includes proximity and habit to meet in person. The approach used for constructing personal (ego-centered) networks on data from the most recent release of Families and Social Subject survey allows us to bring to the foreground people exposed to relational vulnerability. The analysis of the most vulnerable individuals by age, gender, and place of residence reveals that living alone is often associated with a condition of relational vulnerability for both the elderly and for young adults.

Author Posting. © American Meteorological Society, 2022. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of the Atmospheric and Oceanic Technology 39(4), (2022): 491–502, https://doi.org/10.1175/jtech-d-21-0046.1., The Air-Launched Autonomous Micro Observer (ALAMO) is a versatile profiling float that can be launched from an aircraft to make temperature and salinity observations of the upper ocean for over a year with high temporal sampling. Similar in dimensions and weight to an airborne expendable bathythermograph (AXBT), but with the same capability as Argo profiling floats, ALAMOs can be deployed from an A-sized (sonobuoy) launch tube, the stern ramp of a cargo plane, or the door of a small aircraft. Unlike an AXBT, however, the ALAMO float directly measures pressure, can incorporate additional sensors, and is capable of performing hundreds of ocean profiles compared to the single temperature profile provided by an AXBT. Upon deployment, the float parachutes to the ocean, releases the air-deployment package, and immediately begins profiling. Ocean profile data along with position and engineering information are transmitted via the Iridium satellite network, automatically processed, and then distributed by the Global Telecommunications System for use by the operational forecasting community. The ALAMO profiling mission can be modified using the two-way Iridium communications to change the profiling frequency and depth. Example observations are included to demonstrate the ALAMO’s utility., This work was supported by the National Oceanographic and Atmospheric Administration under Grants NA13OAR4830233 (as part of CINAR Sandy Supplemental funding from the Disaster Relief Appropriations Act of 2013) and NA14OAR4320158 and by Office of Naval Research under Grants N0001416WX01384, N0001416WX01262, and N000141512293. ALAMO floats are commercially available from MRV Systems, LLC (https://www.mrvsys.com).

Author Posting. © American Meteorological Society, 2022. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of the Atmospheric and Oceanic Technology 39(4), (2022): 491–502, https://doi.org/10.1175/jtech-d-21-0046.1., The Air-Launched Autonomous Micro Observer (ALAMO) is a versatile profiling float that can be launched from an aircraft to make temperature and salinity observations of the upper ocean for over a year with high temporal sampling. Similar in dimensions and weight to an airborne expendable bathythermograph (AXBT), but with the same capability as Argo profiling floats, ALAMOs can be deployed from an A-sized (sonobuoy) launch tube, the stern ramp of a cargo plane, or the door of a small aircraft. Unlike an AXBT, however, the ALAMO float directly measures pressure, can incorporate additional sensors, and is capable of performing hundreds of ocean profiles compared to the single temperature profile provided by an AXBT. Upon deployment, the float parachutes to the ocean, releases the air-deployment package, and immediately begins profiling. Ocean profile data along with position and engineering information are transmitted via the Iridium satellite network, automatically processed, and then distributed by the Global Telecommunications System for use by the operational forecasting community. The ALAMO profiling mission can be modified using the two-way Iridium communications to change the profiling frequency and depth. Example observations are included to demonstrate the ALAMO’s utility., This work was supported by the National Oceanographic and Atmospheric Administration under Grants NA13OAR4830233 (as part of CINAR Sandy Supplemental funding from the Disaster Relief Appropriations Act of 2013) and NA14OAR4320158 and by Office of Naval Research under Grants N0001416WX01384, N0001416WX01262, and N000141512293. ALAMO floats are commercially available from MRV Systems, LLC (https://www.mrvsys.com).

Using data from the 2016 Family and Social Subjects (FSS) survey and the first wave of the SHARE Corona Survey carried out in 2020, we aimed to depict the social network characteristics of older people in Italy, with a special focus on tracing the changes related to the outbreak of the SARS-CoV-2 virus.

Providing support outside the household can be considered an actual sign of an active social life for the elderly. Adopting an ego–network perspective, we study support Italian elders provide to kin or non–kin. More specifically, using Italian survey data, we build the ego–centered networks of social contacts elders entertain and the ego–networks of support elders provide to other non–cohabitant kin or non–kin. Since ego–network data are inherently multilevel, we use Bayesian multilevel models to analyze variation in support ties, controlling for the characteristics of elders and their contacts. This modeling strategy enables dealing with sparseness and alter–alter overlap in the ego support network data and to disentangle the effects related to the ego (the elder), the dyad ego–alter, the kind of support provided, as well as social contacts and contextual variables. The results suggest that the elderly in Italy who provide support outside their household — compared to all elders in the sample — are younger, healthier, more educated, and embedded in a more diversified ego–network of social contacts. The latter also conveys both the type and the recipient of the support, with the elderly who entertain few relationships with kin being more prone to provide aid to non–kin. Further, a “peer homophily” effect in directing elder support to a non–kin is also found.

The policies for containing the spread of the SARS-CoV2 virus include a number of measures aimed at reducing physical contacts. In this paper, we explore the potential impact of such containment measures on social relations of both young adults and the elderly in Italy. We propose two ego-centered network definitions accounting for physical distance in light of the COVID-19 containment measures: the easy-to-reach network, that represents an accessible source of support that can be activate in case of new lockdown; the accustomed-to-reach network, which includes proximity and habit to meet in person. The approach used for constructing personal (ego-centered) networks on data from the most recent release of Families and Social Subject survey allows us to bring to the foreground people exposed to relational vulnerability. The analysis of the most vulnerable individuals by age, gender, and place of residence reveals that living alone is often associated with a condition of relational vulnerability for both the elderly and for young adults.

This contribution aims at comparing patterns of social support -provided and received- among the elderly population in European countries. Adopting an egocentered network perspective, by means of multivariate techniques for categorical data, we intend to map the ego-support network structures of the elderly, as well as ego-network functional content of provided and received support in the different countries. Individual and country socio-demographic characteristics will be also considered in interpreting results.

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Wong, A. P. S., Wijffels, S. E., Riser, S. C., Pouliquen, S., Hosoda, S., Roemmich, D., Gilson, J., Johnson, G. C., Martini, K., Murphy, D. J., Scanderbeg, M., Bhaskar, T. V. S. U., Buck, J. J. H., Merceur, F., Carval, T., Maze, G., Cabanes, C., Andre, X., Poffa, N., Yashayaev, I., Barker, P. M., Guinehut, S., Belbeoch, M., Ignaszewski, M., Baringer, M. O., Schmid, C., Lyman, J. M., McTaggart, K. E., Purkey, S. G., Zilberman, N., Alkire, M. B., Swift, D., Owens, W. B., Jayne, S. R., Hersh, C., Robbins, P., West-Mack, D., Bahr, F., Yoshida, S., Sutton, P. J. H., Cancouet, R., Coatanoan, C., Dobbler, D., Juan, A. G., Gourrion, J., Kolodziejczyk, N., Bernard, V., Bourles, B., Claustre, H., D'Ortenzio, F., Le Reste, S., Le Traon, P., Rannou, J., Saout-Grit, C., Speich, S., Thierry, V., Verbrugge, N., Angel-Benavides, I. M., Klein, B., Notarstefano, G., Poulain, P., Velez-Belchi, P., Suga, T., Ando, K., Iwasaska, N., Kobayashi, T., Masuda, S., Oka, E., Sato, K., Nakamura, T., Sato, K., Takatsuki, Y., Yoshida, T., Cowley, R., Lovell, J. L., Oke, P. R., van Wijk, E. M., Carse, F., Donnelly, M., Gould, W. J., Gowers, K., King, B. A., Loch, S. G., Mowat, M., Turton, J., Rama Rao, E. P., Ravichandran, M., Freeland, H. J., Gaboury, I., Gilbert, D., Greenan, B. J. W., Ouellet, M., Ross, T., Tran, A., Dong, M., Liu, Z., Xu, J., Kang, K., Jo, H., Kim, S., & Park, H. Argo data 1999-2019: two million temperature-salinity profiles and subsurface velocity observations from a global array of profiling floats. Frontiers in Marine Science, 7, (2020): 700, doi:10.3389/fmars.2020.00700., In the past two decades, the Argo Program has collected, processed, and distributed over two million vertical profiles of temperature and salinity from the upper two kilometers of the global ocean. A similar number of subsurface velocity observations near 1,000 dbar have also been collected. This paper recounts the history of the global Argo Program, from its aspiration arising out of the World Ocean Circulation Experiment, to the development and implementation of its instrumentation and telecommunication systems, and the various technical problems encountered. We describe the Argo data system and its quality control procedures, and the gradual changes in the vertical resolution and spatial coverage of Argo data from 1999 to 2019. The accuracies of the float data have been assessed by comparison with high-quality shipboard measurements, and are concluded to be 0.002°C for temperature, 2.4 dbar for pressure, and 0.01 PSS-78 for salinity, after delayed-mode adjustments. Finally, the challenges faced by the vision of an expanding Argo Program beyond 2020 are discussed., AW, SR, and other scientists at the University of Washington (UW) were supported by the US Argo Program through the NOAA Grant NA15OAR4320063 to the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) at the UW. SW and other scientists at the Woods Hole Oceanographic Institution (WHOI) were supported by the US Argo Program through the NOAA Grant NA19OAR4320074 (CINAR/WHOI Argo). The Scripps Institution of Oceanography's role in Argo was supported by the US Argo Program through the NOAA Grant NA15OAR4320071 (CIMEC). Euro-Argo scientists were supported by the Monitoring the Oceans and Climate Change with Argo (MOCCA) project, under the Grant Agreement EASME/EMFF/2015/1.2.1.1/SI2.709624 for the European Commission.

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Wong, A. P. S., Wijffels, S. E., Riser, S. C., Pouliquen, S., Hosoda, S., Roemmich, D., Gilson, J., Johnson, G. C., Martini, K., Murphy, D. J., Scanderbeg, M., Bhaskar, T. V. S. U., Buck, J. J. H., Merceur, F., Carval, T., Maze, G., Cabanes, C., Andre, X., Poffa, N., Yashayaev, I., Barker, P. M., Guinehut, S., Belbeoch, M., Ignaszewski, M., Baringer, M. O., Schmid, C., Lyman, J. M., McTaggart, K. E., Purkey, S. G., Zilberman, N., Alkire, M. B., Swift, D., Owens, W. B., Jayne, S. R., Hersh, C., Robbins, P., West-Mack, D., Bahr, F., Yoshida, S., Sutton, P. J. H., Cancouet, R., Coatanoan, C., Dobbler, D., Juan, A. G., Gourrion, J., Kolodziejczyk, N., Bernard, V., Bourles, B., Claustre, H., D'Ortenzio, F., Le Reste, S., Le Traon, P., Rannou, J., Saout-Grit, C., Speich, S., Thierry, V., Verbrugge, N., Angel-Benavides, I. M., Klein, B., Notarstefano, G., Poulain, P., Velez-Belchi, P., Suga, T., Ando, K., Iwasaska, N., Kobayashi, T., Masuda, S., Oka, E., Sato, K., Nakamura, T., Sato, K., Takatsuki, Y., Yoshida, T., Cowley, R., Lovell, J. L., Oke, P. R., van Wijk, E. M., Carse, F., Donnelly, M., Gould, W. J., Gowers, K., King, B. A., Loch, S. G., Mowat, M., Turton, J., Rama Rao, E. P., Ravichandran, M., Freeland, H. J., Gaboury, I., Gilbert, D., Greenan, B. J. W., Ouellet, M., Ross, T., Tran, A., Dong, M., Liu, Z., Xu, J., Kang, K., Jo, H., Kim, S., & Park, H. Argo data 1999-2019: two million temperature-salinity profiles and subsurface velocity observations from a global array of profiling floats. Frontiers in Marine Science, 7, (2020): 700, doi:10.3389/fmars.2020.00700., In the past two decades, the Argo Program has collected, processed, and distributed over two million vertical profiles of temperature and salinity from the upper two kilometers of the global ocean. A similar number of subsurface velocity observations near 1,000 dbar have also been collected. This paper recounts the history of the global Argo Program, from its aspiration arising out of the World Ocean Circulation Experiment, to the development and implementation of its instrumentation and telecommunication systems, and the various technical problems encountered. We describe the Argo data system and its quality control procedures, and the gradual changes in the vertical resolution and spatial coverage of Argo data from 1999 to 2019. The accuracies of the float data have been assessed by comparison with high-quality shipboard measurements, and are concluded to be 0.002°C for temperature, 2.4 dbar for pressure, and 0.01 PSS-78 for salinity, after delayed-mode adjustments. Finally, the challenges faced by the vision of an expanding Argo Program beyond 2020 are discussed., AW, SR, and other scientists at the University of Washington (UW) were supported by the US Argo Program through the NOAA Grant NA15OAR4320063 to the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) at the UW. SW and other scientists at the Woods Hole Oceanographic Institution (WHOI) were supported by the US Argo Program through the NOAA Grant NA19OAR4320074 (CINAR/WHOI Argo). The Scripps Institution of Oceanography's role in Argo was supported by the US Argo Program through the NOAA Grant NA15OAR4320071 (CIMEC). Euro-Argo scientists were supported by the Monitoring the Oceans and Climate Change with Argo (MOCCA) project, under the Grant Agreement EASME/EMFF/2015/1.2.1.1/SI2.709624 for the European Commission.

Author Posting. © American Meteorological Society, 2018. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 99 (2018): 513-520, doi:10.1175/BAMS-D-16-0323.1., Seasonally ice-covered marginal seas are among the most difficult regions in the Arctic to study. Physical constraints imposed by the variable presence of sea ice in all stages of growth and melt make the upper water column and air–sea ice interface especially challenging to observe. At the same time, the flow of solar energy through Alaska’s marginal seas is one of the most important regulators of their weather and climate, sea ice cover, and ecosystems. The deficiency of observing systems in these areas hampers forecast services in the region and is a major contributor to large uncertainties in modeling and related climate projections. The Arctic Heat Open Science Experiment strives to fill this observation gap with an array of innovative autonomous floats and other near-real-time weather and ocean sensing systems. These capabilities allow continuous monitoring of the seasonally evolving state of the Chukchi Sea, including its heat content. Data collected by this project are distributed in near–real time on project websites and on the Global Telecommunications System (GTS), with the objectives of (i) providing timely delivery of observations for use in weather and sea ice forecasts, for model, and for reanalysis applications and (ii) supporting ongoing research activities across disciplines. This research supports improved forecast services that protect and enhance the safety and economic viability of maritime and coastal community activities in Alaska. Data are free and open to all (see www.pmel.noaa.gov/arctic-heat/)., This work was supported by NOAA Ocean and Atmospheric Research and the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement NA15OAR4320063 and by the Innovative Technology for Arctic Exploration (ITAE) program at JISAO/PMEL. Jayne, Robbins, and Ekholm were supported by ONR (N00014-12-10110).

Author Posting. © American Meteorological Society, 2018. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 99 (2018): 513-520, doi:10.1175/BAMS-D-16-0323.1., Seasonally ice-covered marginal seas are among the most difficult regions in the Arctic to study. Physical constraints imposed by the variable presence of sea ice in all stages of growth and melt make the upper water column and air–sea ice interface especially challenging to observe. At the same time, the flow of solar energy through Alaska’s marginal seas is one of the most important regulators of their weather and climate, sea ice cover, and ecosystems. The deficiency of observing systems in these areas hampers forecast services in the region and is a major contributor to large uncertainties in modeling and related climate projections. The Arctic Heat Open Science Experiment strives to fill this observation gap with an array of innovative autonomous floats and other near-real-time weather and ocean sensing systems. These capabilities allow continuous monitoring of the seasonally evolving state of the Chukchi Sea, including its heat content. Data collected by this project are distributed in near–real time on project websites and on the Global Telecommunications System (GTS), with the objectives of (i) providing timely delivery of observations for use in weather and sea ice forecasts, for model, and for reanalysis applications and (ii) supporting ongoing research activities across disciplines. This research supports improved forecast services that protect and enhance the safety and economic viability of maritime and coastal community activities in Alaska. Data are free and open to all (see www.pmel.noaa.gov/arctic-heat/)., This work was supported by NOAA Ocean and Atmospheric Research and the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement NA15OAR4320063 and by the Innovative Technology for Arctic Exploration (ITAE) program at JISAO/PMEL. Jayne, Robbins, and Ekholm were supported by ONR (N00014-12-10110).

Author Posting. © The Oceanography Society, 2017. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 30, no. 2 (2017): 92–103, doi:10.5670/oceanog.2017.227., The tropical Atlantic basin is one of seven global regions where tropical cyclones (TCs) commonly originate, intensify, and affect highly populated coastal areas. Under appropriate atmospheric conditions, TC intensification can be linked to upper-ocean properties. Errors in Atlantic TC intensification forecasts have not been significantly reduced during the last 25 years. The combined use of in situ and satellite observations, particularly of temperature and salinity ahead of TCs, has the potential to improve the representation of the ocean, more accurately initialize hurricane intensity forecast models, and identify areas where TCs may intensify. However, a sustained in situ ocean observing system in the tropical North Atlantic Ocean and Caribbean Sea dedicated to measuring subsurface temperature, salinity, and density fields in support of TC intensity studies and forecasts has yet to be designed and implemented. Autonomous and Lagrangian platforms and sensors offer cost-effective opportunities to accomplish this objective. Here, we highlight recent efforts to use autonomous platforms and sensors, including surface drifters, profiling floats, underwater gliders, and dropsondes, to better understand air-sea processes during high-wind events, particularly those geared toward improving hurricane intensity forecasts. Real-time data availability is key for assimilation into numerical weather forecast models., The NOAA/AOML component of this work was originally funded by the Disaster Relief Appropriations Act of 2013, also known as the Sandy Supplemental, and is currently funded through NOAA research grant NA14OAR4830103 by AOML and CARICOOS, as well as NOAA’s Integrated Ocean Observing System (IOOS). The TEMPESTS component of this work is supported by NOAA through the Cooperative Institute for the North Atlantic Region (NA13OAR4830233) with additional analysis support from the WHOI Summer Student Fellowship Program, Nortek Student Equipment Grant, and the Rutgers University Teledyne Webb Graduate Student Fellowship Program. The drifter component of this work is funded through NOAA grant NA15OAR4320071(11.432) in support of the Global Drifter Program.

Author Posting. © The Oceanography Society, 2017. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 30, no. 2 (2017): 92–103, doi:10.5670/oceanog.2017.227., The tropical Atlantic basin is one of seven global regions where tropical cyclones (TCs) commonly originate, intensify, and affect highly populated coastal areas. Under appropriate atmospheric conditions, TC intensification can be linked to upper-ocean properties. Errors in Atlantic TC intensification forecasts have not been significantly reduced during the last 25 years. The combined use of in situ and satellite observations, particularly of temperature and salinity ahead of TCs, has the potential to improve the representation of the ocean, more accurately initialize hurricane intensity forecast models, and identify areas where TCs may intensify. However, a sustained in situ ocean observing system in the tropical North Atlantic Ocean and Caribbean Sea dedicated to measuring subsurface temperature, salinity, and density fields in support of TC intensity studies and forecasts has yet to be designed and implemented. Autonomous and Lagrangian platforms and sensors offer cost-effective opportunities to accomplish this objective. Here, we highlight recent efforts to use autonomous platforms and sensors, including surface drifters, profiling floats, underwater gliders, and dropsondes, to better understand air-sea processes during high-wind events, particularly those geared toward improving hurricane intensity forecasts. Real-time data availability is key for assimilation into numerical weather forecast models., The NOAA/AOML component of this work was originally funded by the Disaster Relief Appropriations Act of 2013, also known as the Sandy Supplemental, and is currently funded through NOAA research grant NA14OAR4830103 by AOML and CARICOOS, as well as NOAA’s Integrated Ocean Observing System (IOOS). The TEMPESTS component of this work is supported by NOAA through the Cooperative Institute for the North Atlantic Region (NA13OAR4830233) with additional analysis support from the WHOI Summer Student Fellowship Program, Nortek Student Equipment Grant, and the Rutgers University Teledyne Webb Graduate Student Fellowship Program. The drifter component of this work is funded through NOAA grant NA15OAR4320071(11.432) in support of the Global Drifter Program.

In this paper, a log-linear multidimensional Rasch model is proposed for capture-recapture analysis of registration data. In the model, heterogeneity of capture probabilities is taken into account, and registrations are viewed as dichotomously scored indicators of one or more latent variables that can account for correlations among registrations. It is shown how the probability of a generic capture profile is expressed under the log-linear multidimensional Rasch model and how the parameters of the traditional log-linear model are derived from those of the log-linear multidimensional Rasch model. Finally, an application of the model to neural tube defects data is presented.

The traditional capture-recapture method assumes homogeneity of the capture probabilities. However, differences of character or behaviour between individuals may occur and models that allow for varying susceptibility to capture over individuals and unequal catchability have been proposed and psychometric models, such as the Rasch model, were successfully applied. In the present work, we propose the use of the multidimensional Rasch model in the capture-recapture context. We assume that lists may be divided into two or more subgroups, such that they can be viewed as indicators of the latent variables which account for correlations among lists. We show how to express the probability of a generic capture profile in terms of log-linear multidimensional Rasch model and apply the methodology to a real data set.

One of the most important task for epidemiologists, biologists, ecologists and sociologists is to analyse and forecast possible changes and dynamics in a population. Capture-recapture experiments may be used to obtain meaningful information from population under study. The rational behind this method is to account for unobserved individuals by using observed individual trapping histories. A central assumption in traditional capture-recapture approach is the homogeneity of the capture probability. However, differences of character or behaviour between individuals may occur and this fact results in indirect dependence between registrations. Psychometric models, such as the Rasch model, may be successfully applied. We propose the use of the multidimensional Rasch model in the capture-recapture context. In particular, we assume that registrations may be divided into two or more subgroups, such that they can be view as indicators of the latent variables which account for correlations among registrations. To do so, the extension of the Dutch Identity for the multidimensional partial credit model can be utilized. It allows us to express the multidimensional Rasch model in a log-linear representation and to derive the parameters of the traditional log-linear model from those of the multidimensional Rasch model.