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Random survival forest
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Journal Article
Demography (2021) 58 (1): 137–163.
Published: 01 February 2021
... that is due to the structural change in the hazard functions. This decomposition is achieved by employing the random survival forest, allowing me to predict the counterfactual infant survival probability that infants in the 2010s would have under the circumstantial environments of the 1990s. The results show...
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Journal Article
Demography (2022) 59 (1): 161–186.
Published: 01 February 2022
...Bruno Arpino; Marco Le Moglie; Letizia Mencarini Abstract This study contributes to the literature on union dissolution by adopting a machine learning (ML) approach, specifically Random Survival Forests (RSF). We used RSF to analyze data on 2,038 married or cohabiting couples who participated...
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in What Tears Couples Apart: A Machine Learning Analysis of Union Dissolution in Germany
> Demography
Published: 01 February 2022
Fig. 1 Variable importance (VIMP) measures for all 35 independent variables included as predictors in the Random Survival Forests
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Journal Article
Demography (2014) 51 (3): 811–834.
Published: 25 April 2014
... application in modeling survival time data (Powers and Xie 2008 ). The random-effects terms in our models also help alleviate the problems of overdispersion and excess zeros often encountered in conventional Poisson models (Rabe-Hesketh and Skrondal 2012 ). As a robustness check, we repeated our regression...
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Journal Article
Demography (2010) 47 (4): 963–987.
Published: 01 November 2010
... in our sample are observed 1.9 times across three time periods. As explained later in this article, we use random effects models, which allow for data that are unbalanced in time by including all households in its estimation, regardless of their attrition status or the number of waves they contribute...
Journal Article
Demography (2007) 44 (4): 747–770.
Published: 01 November 2007
... of discrete-time, event-history methods the multilevel, random-effects, discrete-time hazard model. Barber et al. (2000) showed that it is possible to use any maximum likelihood estimator for this model conditional on four assumptions: (1) the hazard probability for each respondent is independent...
Journal Article
Demography (1999) 36 (3): 355–367.
Published: 01 August 1999
..., all analytical results obtained for this re- search are based on simple random sample methods. Hypoth- esis tests may show less significance and confidence inter- vals may be wider due to larger variances if analyses take into account the complex design. Previous results for deter- mining point...
Journal Article
Demography (2017) 54 (6): 2125–2158.
Published: 21 November 2017
... ). Approximately 75 % of the sample has three or more observations of fluid cognition. These growth curve models are two-level hierarchical models with individuals at Level 2, individuals’ multiple fluid cognition scores at Level 1, and a random coefficient for Cohort : 1 Y it = α + β 1 i Age...
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Journal Article
Demography (2006) 43 (1): 99–125.
Published: 01 February 2006
... at least as educated as their wives. This pattern is produced largely by gender differences in educational distributions. (A random mixing pattern with the underlying educational distributions of husbands and wives would yield 16.7% of wives more educated than their husbands, compared with the prevailing...
Journal Article
Demography (2006) 43 (4): 727–746.
Published: 01 November 2006
... to different family-speci c factors (biological or behavioral) that are not controlled for in the models. The large number of families in the data does not allow us to estimate xed family effects. Instead, we add frailty effects (or random effects) to our survival models in order to control...
Journal Article
Demography (2003) 40 (2): 217–245.
Published: 01 May 2003
... is the assumption re- garding sexual mixing patterns (Anderson et al. 1991; Garnett and Anderson 1993). Simu- lations demonstrate that the more individuals tend to choose partners similar to themselves that is, the less random the mixing pattern the more quickly the epi- demic growth rate tapers off (Brookmeyer...
Journal Article
Demography (2005) 42 (4): 791–812.
Published: 01 November 2005
... and Ord 1981). Moran s I is the most commonly used univariate statistic to test spatially arrayed data for spatial autocorrelation against a null hypothesis of total spatial randomness. Moran s I is expressed as I w y y y kl i j ij ikl kl jkl kl ikl kli = ( ) ( ) ( 2 , where wij is an element...
Journal Article
Demography (2019) 56 (4): 1389–1425.
Published: 19 July 2019
..., we define the influenza period using alternate thresholds and setting the individual’s date of birth to occur on the first, the last, or a random day of the month. The main analyses consider the influenza pandemic to have started in the month when the county-level crude mortality exceeded 1.75...
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Journal Article
Demography (1967) 4 (1): 30–70.
Published: 01 March 1967
... Backwardness and Economic Growth . NewYork : John Wiley . 38 Wrong Dennis H. ( 1962 ). Population and Society (pp. 18 – 50 ). New York : Random House . 39 The case of France may be an exception (see United Nations, The Determinants … , p. 81. 40 Leibenstein H. ( 1957...
Journal Article
Demography (2021) 58 (2): 499–526.
Published: 01 April 2021
... also use multilevel regression models and conduct two separate models. We nest individuals within clusters in one model, and we nest individuals within mothers. In other words, we treat the cluster or the mother as a random effect. No significant difference in our findings results from these different...
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Journal Article
Demography (2017) 54 (6): 2351–2374.
Published: 21 November 2017
... couples in random samples, early U.S. studies were based on convenience samples (Blumstein and Schwartz 1983 ; Kurdek 1998 , 2004 ). Some recent U.S. studies relied on population-based samples (i.e., Badgett and Herman 2013 ; Balsam et al. 2008 ; Gates 2006 ; Manning et al. 2016 ; Rosenfeld 2014...
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Journal Article
Demography (2016) 53 (5): 1511–1534.
Published: 16 August 2016
... of dummy variables for the year (not shown in the tables). No other predictors need to be included in order to estimate the independent effect of hurricane damage, which we interpret here as a random exogenous shock. Table 2 reports models for change in total population, white and black populations...
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Journal Article
Demography (2020) 57 (3): 953–977.
Published: 05 May 2020
... important because it provides a precise measure of the population at risk. The study population is not a random sample of Sweden but is broadly representative by reflecting conditions shared by populations in similar areas during the time studied (see Bengtsson 2004 ; Dribe and Helgertz 2016 ; Dribe et al...
Journal Article
Demography (1965) 2 (1): 140–186.
Published: 01 March 1965
... per woman aged 15--49, standard- ized for age, was equal to 2.90 in Aswan and 3.57 in Giza. The 1947 data also indicate that the variation in parity in the non urban gov- ernorates of Lower Egypt is again not random but has a general upward trend from west to east and from south to north. Thus Behera...
