Sentences with phrase «survival analysis models»

Not exact matches

Kaplan - Meier and Cox proportional hazards survival analyses were used in unadjusted and adjusted analyses of the effect of pacifier use on breastfeeding duration.19 Logistic regression modeling was used to evaluate the effect of pacifier timing on breastfeeding duration.20 Significance levels were not adjusted for multiple comparisons.

«The Dam Impact Analysis Model provides managers with a way to assess the levels of survival needed for Atlantic salmon at several large mainstem dams in the lower Penobscot River,» said Jeff Murphy, an endangered species biologist at GARFO.

«The Dam Impact Analysis Model enables us to see what happens when you change one factor, like marine or freshwater survival,» said Julie Nieland, a researcher at NEFSC's laboratory in Woods Hole, Mass. and lead author of the study.

Hirofumi Michimae, Ayumi Tezuka, Takeshi Emura & Osamu Kishida — 2014 (7)([email protected]) Keywords: competing risk, Cox proportional hazards model, metamorphosis, survival analysis

Using robust design analysis of multi-season data, we developed several models to understand the effects of different variables on the modelled parameters that included survival probability, temporary emigration and immigration, and capture and recapture probabilities.

We then evaluated whether the encapsulation of hPSC - CDH5 + cells in PA - RGDS could enhance long - term cell survival and vascular regenerative effects in a hind - limb ischemia model with laser Doppler perfusion imaging, bioluminescence imaging, real - time reverse transcription - polymerase chain reaction, and histological analysis.

An Interview with Conant Professor Judith Singer and Eliot Professor John Willett Applied statisticians and long - time research partners Conant Professor Judith Singer and Eliot Professor John Willett recently published Applied Longitudinal Data Analysis, which offers an integrated treatment of individual growth modeling and survival aAnalysis, which offers an integrated treatment of individual growth modeling and survival analysisanalysis.

«Modeling the Days of Our Lives: Using Survival Analysis When Designing and Analyzing Longitudinal Studies of Duration and the Timing of Events,» in Psychological Bulletin (with J.D. Singer), (1991)

Focusing on two complementary longitudinal methods — individual growth modeling and survival analysis — Willett and Singer provide new avenues for researchers to address critical questions about how things evolve and how long it takes for change to occur.

Given that impacts don't scale linearly — that's true both because of the statistics of normal distributions, which imply that (damaging) extremes become much more frequent with small shifts in the mean, and because significant breakpoints such as melting points for sea ice, wet - bulb temperatures too high for human survival, and heat tolerance for the most significant human food crops are all «in play» — the model forecasts using reasonable emissions inputs ought to be more than enough for anyone using sensible risk analysis to know that we making very bad choices right now.

Another is population viability analysis, which uses computer models to project trends in a range of conditions affecting isolated populations of a species and calculates the probability of long - time survival.

In their first USGS report, the authors demonstrated high integrity in their analysis and were upfront about the problems of their models writing, «the declines we observed in model - averaged survival rates may reflect an increase in the number of «emigrants» toward the end of the study, and not an actual decrease in biological survival».

Survival analysis, Data imputation, Mixed models, GEEs, Propensity score matching, Sample size calculations, occasional genetic analysis

Performed advanced statistical analysis (univariate and multivariate analysis of variance, cluster and path analysis, principle component and factor analysis, analysis of covariance, survival & longitudinal analysis, logistic and linear regression modeling), created customized reports and presentation quality data summary tables and figures.

Discrete - time survival analysis, with person - year the unit of analysis and a logistic link function, was used to examine associations of temporally primary (based on retrospective age - at - onset reports) mental disorders and subsequent first onset of suicidality.29 Time was modeled as a separate dummy predictor variable for each year of life up to age at interview or age at onset of the outcome, whichever came first.

Articles discuss methodological challenges and opportunities in family and couple research, including outcome, cost - effectiveness, qualitative, and narrative research; video - recall procedures, multilevel methods, diary methods, and cluster analysis; and moderator effects, the actor — partner interdependence model, survival analysis, and ethical issues.

The association between suicidality and childhood adversity was examined using discrete - time survival models with the analysis unit being person - years.