We consider a continuous-time, ergodic Markov process on a large continuous or discrete state space. The process is assumed to exhibit a number of metastable sets. Markov state models (MSMs) are designed to represent the effective dynamics of such a process by a Markov chain that jumps between the metastable sets with the transition rates of the original process. MSMs have been used for a numbe...

Markov state models of molecular kinetics (MSMs), in which the long-time statistical dynamics of a molecule is approximated by a Markov chain on a discrete partition of configuration space, have seen widespread use in recent years. This approach has many appealing characteristics compared to straightforward molecular dynamics simulation and analysis, including the potential to mitigate the samp...

One of the main objectives in clinical epidemiology is to detect a relation between treatment and outcome. We address data where treatment is applied repeatedly in time and the dose given at a specific time-point may be modified due to actual measurements on disease parameters. If such measurements are subsequently affected by the treatment, they might act as time-dependent confounders. Standar...

BACKGROUND Vitamin D is important to health and disease. Liquid chromatography-tandem mass spectrometry (LC-MSMS) is considered the most accurate technology for quantification of serum 25-hydroxyvitamin D (25OHD) which is the best biomarker for estimating vitamin D nutritional status. METHODS Serum was mixed with acetonitrile containing hexadeuterated 25-hydroxyvitamin D(3) (d(6)-25OHD3) and ...

PURPOSE Results from longitudinal studies about the association between physical activity and chronic obstructive pulmonary disease (COPD) may have been biased because they did not properly adjust for time-dependent confounders. Marginal structural models (MSMs) have been proposed to address this type of confounding. We sought to assess the presence of time-dependent confounding in the associat...

Standard statistical analyses of observational data often exclude valuable information from individuals with incomplete measurements. This may lead to biased estimates of the treatment effect and loss of precision. The issue of missing data for inverse probability of treatment weighted estimation of marginal structural models (MSMs) has often been addressed, though little has been done to compa...

Differential proteomic analysis has arisen as a large-scale means to discern proteome-wide changes upon treatment, injury, or disease. Tandem protein separation methods are required for large-scale differential proteomic analysis. Here, a novel multidimensional platform for resolving and differentially analyzing complex biological samples is presented. The platform, collectively termed CAX-PAGE...

The determination of the current antiblastic drug contamination levels in an Italian hospital oncology ward was carried out. Statistical evaluation of data aiming to identify potential exposure causes was performed. Cyclophosphamide (CP), ifosfamide (IF) and 5-fluorouracil (5-FU) were determined by wipe tests, extracted with diatomaceous earths and quantified by GC/MSMS or HPLC/UV. Data were an...

In assessing the efficacy of a time-varying treatment Marginal Structural Models (MSMs) and Structural Nested Mean Models (SNMMs) are useful in dealing with confounding by variables affected by earlier treatments. MSMs model the joint effect of treatments on the marginal mean of the potential outcome, whereas SNMMs model the joint effect of treatments on the mean of the potential outcome condit...