Results 231 to 240 of about 4,270,888 (278)

Conditional autoregressive model based on next scale prediction for missing data reconstruction. [PDF]

Sci Rep
Wang S, Wang X, Yang Y, Jiang P, Wang B, Li Y.   +5 more
europepmc   +1 more source

Biomimetic model for computing missing data imputation and inconsistency reduction in pairwise comparisons matrices. [PDF]

PLoS One
Koczkodaj WW, Pedrycz W, Pigazzini A, Pigazzini LP.   +3 more
europepmc   +1 more source

Impute the missing data by combining retrieved dropouts and return to baseline method. [PDF]

PLoS One
Li X, Yang Z, Yuan C, Liu J, Li Z.
europepmc   +1 more source

Bridging the Gap: Missing Data Imputation Methods and Their Effect on Dementia Classification Performance. [PDF]

Brain Sci
Aracri F, Bianco MG, Quattrone A, Sarica A.   +3 more
europepmc   +1 more source

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Missing Data

Organizational Research Methods, 2014
Missing data (a) reside at three missing data levels of analysis (item-, construct-, and person-level), (b) arise from three missing data mechanisms (missing completely at random, missing at random, and missing not at random) that range from completely random to systematic missingness, (c) can engender two missing data problems (biased parameter ...
exaly   +2 more sources

Missing Data

Journal of Nursing Education, 2022
If left unattended, missingness can undermine the conclusions nurse researchers draw in their studies. Unfortunately, a cursory review of quantitative and mixed methods works recently published in the Journal of Nursing Education suggests missing data is left relatively unattended within our community.
Abdulaziz, Abaoud, John M, Taylor
openaire   +2 more sources

The Case of the Missing Data

NEJM Evidence, 2022
The Case of the Missing DataThis animated video explores how investigators approach missing data in clinical trials.
Katherine S, Takvorian, Chana A, Sacks, Charles C, Hardin   +2 more
openaire   +2 more sources