Analysis of Binary Multivariate Longitudinal Data via 2-Dimensional Orbits: An Application to the Agincourt Health and Socio-Demographic Surveillance System in South Africa.
Analysis of Binary Multivariate Longitudinal Data via 2-Dimensional Orbits: An Application to the Agincourt Health and Socio-Demographic Surveillance System in South Africa.
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DOI：
10.1371/journal.pone.0123812
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Cromieres F
中科院分区：
文献类型：
--
作者：
Visaya MV;Sherwell D;Sartorius B;Cromieres F
我们分析了南非阿金库尔卫生和社会人口监测系统对南非(SA)和莫桑比克(MOZ)农村家庭的人口纵向调查数据。特别是，我们确定绝对贫困状况(APS)是否与选定的与社会经济决定有关的家庭变量有关，即家庭户主年龄、家庭规模、累计死亡人数、成年人与未成年人的比例以及人口流入。为了便于比较，家庭按户主国籍(SA或MOZ)和APS(富裕或贫穷)进行分类。四个子群(SA富人、SA穷人、Moz富人和Moz穷人)中每一个的纵向数据是由二元变量(问题)、受试者和时间定义的五维空间。我们使用轨道方法将每个家庭的二进制多变量纵向数据(BMLD)表示为二维轨道，并可视化人口的动态和行为。在每个时间步长，来自家庭轨道的一个点(x，y)对应于家庭的观察，其中x是响应的二进制序列，y是变量的排序。变量的排序被动态地重新排列，使得分别与状态空间中变化最少和最频繁的变量相关联的簇和空穴被暴露。对轨道的分析揭示了个人和群体水平上的变化信息、数据中的变化模式、状态空间中的状态容量以及轨道中的状态转移密度。对四个亚群的家庭轨道的分析表明，(一)以老年人和富裕家庭为户主的家庭，(二)大家庭和贫困家庭，以及(三)未成年人多于成年人和贫困家庭的家庭。将我们的结果与其他BMLD分析方法进行了比较。
We analyse demographic longitudinal survey data of South African (SA) and Mozambican (MOZ) rural households from the Agincourt Health and Socio-Demographic Surveillance System in South Africa. In particular, we determine whether absolute poverty status (APS) is associated with selected household variables pertaining to socio-economic determination, namely household head age, household size, cumulative death, adults to minor ratio, and influx. For comparative purposes, households are classified according to household head nationality (SA or MOZ) and APS (rich or poor). The longitudinal data of each of the four subpopulations (SA rich, SA poor, MOZ rich, and MOZ poor) is a five-dimensional space defined by binary variables (questions), subjects, and time. We use the orbit method to represent binary multivariate longitudinal data (BMLD) of each household as a two-dimensional orbit and to visualise dynamics and behaviour of the population. At each time step, a point (x, y) from the orbit of a household corresponds to the observation of the household, where x is a binary sequence of responses and y is an ordering of variables. The ordering of variables is dynamically rearranged such that clusters and holes associated to least and frequently changing variables in the state space respectively, are exposed. Analysis of orbits reveals information of change at both individual- and population-level, change patterns in the data, capacity of states in the state space, and density of state transitions in the orbits. Analysis of household orbits of the four subpopulations show association between (i) households headed by older adults and rich households, (ii) large household size and poor households, and (iii) households with more minors than adults and poor households. Our results are compared to other methods of BMLD analysis.
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影响因子：
5.4
作者：
Hubbard, Alan E.;Ahern, Jennifer;Satariano, William A.
通讯作者：
Satariano, William A.
DOI：
10.1080/03610910701539617
发表时间：
2007-01-01
影响因子：
0.9
作者：
Cui, James;Qian, Guoqi
通讯作者：
Qian, Guoqi
影响因子：
1.9
作者：
Pan, W
通讯作者：
Pan, W
影响因子：
2.3
作者：
Luo S;Lawson AB;He B;Elm JJ;Tilley BC
通讯作者：
Tilley BC
影响因子：
2.6
作者：
Collinson MA
通讯作者：
Collinson MA