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The ghosts of departed quantities: approaches to dealing with observations below the limit of quantitation
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Outgoing claims: the papers this work cites, builds on, or argues with.
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TESTING FOR TREATMENT DIFFERENCES WITH DROPOUTS PRESENT IN CLINICAL TRIALS - A COMPOSITE APPROACH
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Missing Data in Clinical Studies
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Evaluation of Uncertainty Parameters Estimated by Different Population PK Software and Methods
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Impact of censoring data below an arbitrary quantification limit on structural model misspecification
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Likelihood based approaches to handling data below the quantification limit using NONMEM VI
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Impact of low percentage of data below the quantification limit on parameter estimates of pharmacokinetic models
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Theory of Statistical Estimation
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Ways to Fit a PK Model with Some Data Below the Quantification Limit
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Commentary on Significance Levels for Covariate Effects in NONMEM
inferredcites →https://doi.org/10.1080/01621459.1949.10483324openalex-snapshot
On Estimating the Mean and Standard Deviation of Truncated Normal Distributions
inferredcites →https://doi.org/10.1080/01621459.1993.10594302openalex-snapshot
Pattern-Mixture Models for Multivariate Incomplete Data
inferredcites →https://doi.org/10.1093/biomet/44.1-2.225openalex-snapshot
ON THE SOLUTION OF ESTIMATING EQUATIONS FOR TRUNCATED AND CENSORED SAMPLES FROM NORMAL POPULATIONS
inferredcites →https://doi.org/10.1093/biomet/6.1.59openalex-snapshot
ON THE GENERALISED PROBABLE ERROR IN MULTIPLE NORMAL CORRELATION
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Double Hierarchical Generalized Linear Models (With Discussion)
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Observational Study of the Clinical Efficacy of Voriconazole and Its Relationship to Plasma Concentrations in Patients
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Handling Data Below the Limit of Quantification in Mixed Effect Models
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Estimating the Mean and Variance of Normal Populations from Singly Truncated and Doubly Truncated Samples
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Nondetects and Data Analysis: Statistics for Censored Environmental Data
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Estimation of Relationships for Limited Dependent Variables
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Estimating Treatment Effects in Clinical Trials Subject to Regression to the Mean
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