We have grouped features dedicated to OMICs data analysis, dose effect analysis and method validation and proficiency testing in a single menu for quicker access. New menu in the XLSTAT ribbon for laboratory data analysis.There are also many applications in the actuarial field to calculate the cost of insurance and viatical contracts.įor example, we can use this method to model the transition between the healthy, dementia and death states and evaluate the effect of demographic factors on these transitions.Īccess this new feature under the Survival Data Analysis menu. This model is frequently used in medical applications and research to analyze disease evolution or mortality. It allows us to analyze survival-time data and to model the movement of individuals among the different states, such as: The illness-death models are a special case of multistate models with 3 states: the initial state, the transient state and the absorbing state. Among the XLSTAT outputs, we can find the homoscedasticity plot which compares location and scale and helps us identify potential outliers.Īccess this new feature under the Laboratory Data Analysis menu. We need to assess the performance of measurement taking and define to what extent the proficiency standards have been met by the laboratories. Proficiency testing can be performed to assess the performance of laboratories making measurements, to detect problems in one or more laboratories when they arise, or to establish effectiveness and comparability of different methods.Ī simple example: 29 laboratories measured the concentrations of antibodies for two similar allergens. More information on the identified errors and the corrections applied by our R&D team are available in this article. As some errors have been detected in this edition, XLSTAT also lets you run the analysis including the errors. It was first developed using the 2015 edition of ISO-13528 standard. This XLSTAT tool evaluates and compares the measurements made by several participants such as laboratories, inspection bodies, or individuals.
What is Inter-laboratory Proficiency Testing? This new version offers new features for biologists, ecologists, medical researchers or anyone who analyzes life sciences data. Those new features are available in XLSTAT Premium and Life Sciences solutions. The results show that in this particular study area, Level 1 models, even BDF, are quite accurate, but the above modelling strategy maximises the extracted information from the local data and BMA reveals that the higher uncertainties occur at areas with higher vulnerability whereas lower uncertainties are observed at areas with lower vulnerabilities.A new version for XLSTAT Life Sciences and Premium users is now available. The model performance is tested by using the nitrate-N concentrations measured for the aquifer. BMA is naturally an Inclusive Multiple Modelling (IMM) strategy at two levels at Level 1 multiple models are constructed and the paper constructs three AI (Artificial Intelligence) models, which comprise ANN (Artificial Neural Network), GEP (Gene Expression Programming), and SVM (Support Vector Machines) but their outputs are fed to the next level model at Level 2, BMA combines ANN, GEP and SVM (the Level 1 models) to quantify their inherent uncertainty in terms of within and in-between model errors. Bayesian Model Averaging (BMA) is used to study inherent uncertainties using the Basic DRASTIC Framework (BDF) for assessing the groundwater vulnerability in a study area related to Lake Urmia.