Comparison of Nested Models for Multiply Imputed Data

2015 ◽  
pp. 451-464
Author(s):  
Yoonsun Jang ◽  
Zhenqiu Lu ◽  
Allan Cohen
Keyword(s):  
Nested Models ◽  
Multiply Imputed

scholarly journals An Alternative Promotion Time Cure Model with Overdispersed Number of Competing Causes: An Application to Melanoma Data

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1815
Author(s):  
Diego I. Gallardo ◽  
Mário de Castro ◽  
Héctor W. Gómez
Keyword(s):  
Estimation Method ◽  
Selection Criterion ◽  
Likelihood Method ◽  
Simulation Studies ◽  
Cure Rate ◽  
Nested Models ◽  
Proposed Model ◽  
The Em Algorithm ◽  
Competing Causes ◽  
The One

A cure rate model under the competing risks setup is proposed. For the number of competing causes related to the occurrence of the event of interest, we posit the one-parameter Bell distribution, which accommodates overdispersed counts. The model is parameterized in the cure rate, which is linked to covariates. Parameter estimation is based on the maximum likelihood method. Estimates are computed via the EM algorithm. In order to compare different models, a selection criterion for non-nested models is implemented. Results from simulation studies indicate that the estimation method and the model selection criterion have a good performance. A dataset on melanoma is analyzed using the proposed model as well as some models from the literature.

Assessing sample size and variable number in multivariate data, with specific reference to cone morphology variation in a population of Picea sitchensis

1985 ◽  
Vol 63 (2) ◽  
pp. 232-241 ◽  
Author(s):  
Rob Scagel ◽  
Y. A. El-Kassaby ◽  
J. Emanuel
Keyword(s):  
Sample Size ◽  
Multivariate Data ◽  
Variable Number ◽  
Picea Sitchensis ◽  
Interindividual Variation ◽  
Specific Reference ◽  
Size Estimation ◽  
Pilot Studies ◽  
Nested Models ◽  
Cone Morphology

A multivariate extension of univariate sample size estimation is outlined that enables one to determine sample size for a multivariate study. The procedure is presented and illustrated by application to intraindividual and interindividual variation of cone morphology in a population of Picea sitchensis (Bong.) Carr. The method involves the stabilization of a scalar estimate of the structure of the correlation matrix (the determinant) among variables for a given sample size. The sample-specific dependency of previously described methods is avoided by random selection of several replicates in nonstructured and structured (nested) models. The procedure is best applied in pilot studies where it can aid in the characterization of multivariate data prior to analysis. Additionally, repeatability estimates for cone scale morphology are presented.

Effects of light, temperature and population variability on the germination of seven Spanish pines

2002 ◽  
Vol 12 (4) ◽  
pp. 261-271 ◽  
Author(s):  
A. Escudero ◽  
F. Pérez-García ◽  
A. L. Luzuriaga
Keyword(s):  
Habitat Preferences ◽  
Population Variability ◽  
Nested Models ◽  
Germination Response ◽  
Germination Characteristics ◽  
Different Populations ◽  
Effects Of Temperature ◽  
Germination Traits ◽  
The Relationship ◽  
Pine Species

AbstractMost Pinus species are obligate seeders. Thus, knowledge of germination characteristics can help in the understanding, prediction and manipulation of the regeneration and dynamics of pine forests. Seven pine species with contrasting habitat preferences and different genetic pairwise distances are present in the Iberian Peninsula and the Canary Islands: P. halepensis, P. nigra, P. pinaster, P. pinea, P. sylvestris, P. uncinata and P. canariensis. These seven pine species comprise an exceptional experimental set to test some questions related to germination traits, such as: (1) What are the effects of light and temperature on germination, taking into account interpopulation variability? (2) Is there any association of germination traits with habitat (montane versus lowland) preferences? and (3) What is the relationship between germination traits and the genetic distance between pine species? P. nigra, P. sylvestris and P. uncinata seeds showed faster germination rates. Seeds of P. nigra and P. sylvestris reached high total germination percentages in every temperature and light treatment, suggesting an opportunistic germination strategy. Unlike montane pines, lowland pines did show significant effects of temperature on germination response: final germination was higher between 15°C and 20°C than at warmer and alternating temperatures. Relatively low temperatures associated with the winter rainy season would favour germination of most of these species. Nested models showed that population variability was the main source of variation in germination response. Thus, there is no phylogenetic control of the germination response and, surprisingly, germination traits were not related to habitat preferences. As a consequence, we believe that studies of the germination characteristics of a pine species should consider different populations.

scholarly journals Both Freud and Hoffman are Right: Anxious-Aggressive and Empathic Dimensions of Guilt

2008 ◽  
Vol 11 (1) ◽  
pp. 159-171 ◽  
Author(s):  
Itziar Etxebarria ◽  
Pedro Apodaca
Keyword(s):  
Young Adults ◽  
Subjective Experience ◽  
Negative Emotions ◽  
The Other ◽  
Point Scale ◽  
Nested Models ◽  
Proposed Model ◽  
Better Than

The purpose of the study was to confirm a model which proposed two basic dimensions in the subjective experience of guilt, one anxious-aggressive and the other empathic, as well as another dimension associated but not intrinsic to it, namely, the associated negative emotions dimension. Participants were 360 adolescents, young adults and adults of both sexes. They were asked to relate one of the situations that most frequently caused them to experience feelings of guilt and to specify its intensity and that of 9 other emotions that they may have experienced, to a greater or lesser extent, at the same time on a 7-point scale. The proposed model was shown to adequately fit the data and to be better than other alternative nested models. This result supports the views of both Freud and Hoffman regarding the nature of guilt, contradictory only at a first glance.

scholarly journals Multiply-Imputed Synthetic Data: Advice to the Imputer

2017 ◽  
Vol 33 (4) ◽  
pp. 1005-1019 ◽  
Author(s):  
Bronwyn Loong ◽  
Donald B. Rubin
Keyword(s):  
Multiple Imputation ◽  
Synthetic Data ◽  
Complete Data ◽  
Actual Data ◽  
Design Information ◽  
Statistical Inferences ◽  
Data Analyses ◽  
Statistical Agencies ◽  
Data Analytic ◽  
Multiply Imputed

AbstractSeveral statistical agencies have started to use multiply-imputed synthetic microdata to create public-use data in major surveys. The purpose of doing this is to protect the confidentiality of respondents’ identities and sensitive attributes, while allowing standard complete-data analyses of microdata. A key challenge, faced by advocates of synthetic data, is demonstrating that valid statistical inferences can be obtained from such synthetic data for non-confidential questions. Large discrepancies between observed-data and synthetic-data analytic results for such questions may arise because of uncongeniality; that is, differences in the types of inputs available to the imputer, who has access to the actual data, and to the analyst, who has access only to the synthetic data. Here, we discuss a simple, but possibly canonical, example of uncongeniality when using multiple imputation to create synthetic data, which specifically addresses the choices made by the imputer. An initial, unanticipated but not surprising, conclusion is that non-confidential design information used to impute synthetic data should be released with the confidential synthetic data to allow users of synthetic data to avoid possible grossly conservative inferences.

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