Using computer simulation data and a real-life dataset collected in China, we show that erroneous conclusions may be drawn even when the predictor, the mediator, and outcome variables are measured at different time waves under the time-lagged model. We propose a more appropriate procedure to use...
the final sample comprised 233 employees pertaining to 63 work groups. The mean size of the teams was 12 members (SD = 14.39). Leaders responded to the same questionnaires but were not considered in the data analyses. The participants’ average ...
Analysis of gene expression data can help to find the time-lagged co-regulation of gene cluster. However, existing method just solve the problem under the condition when the data is discrete number. In this paper, we propose efficient algorithm to indentify time-lagged co-regulated gene cluster...
Since expression regulation is dynamic, time-course data can be used to infer causality, but these datasets tend to be short or sparsely sampled. In addition, temporal methods typically assume that the expression of a gene at a time point depends on the expression of other genes at only the...
Furthermore, the time-lagged data supports prospective influence of perceived safety commitment leadership behaviors on employee safety voice behaviors, suggesting that construction site managers should be trained and supported in consistently encouraging safe behaviors and in interrupting risk behaviors, in ...
2. Data and Methods 2.1. Study Area In this study, the LYR is defined as the reach beginning from Xiaolangdi station and flowing for approximately 880 km across the North China plain, as depicted in Figure 1. This region holds significant importance as one of the major agricultural developmen...
Welcome to Tempo: timeseries manipulation for Spark. This project builds upon the capabilities ofPySparkto provide a suite of abstractions and functions that make operations on timeseries data easier and highly scalable. NOTEthat the Scala version of Tempo is now deprecated and no longer in develop...
Most clinical and biomedical data contain missing values. A patient's record may be split across multiple institutions, devices may fail, and sensors may not be worn at all times. While these missing values are often ignored, this can lead to bias and error when the data are mined. Further...
(CV) set, and a test set. The entire dataset is usually randomized first. The training data is used to update the weights in the network. The test data is then used to assess how well the network has generalized. The learning and generalization ability of the estimated NN model is ...
Modeling Complexity of EMA Data: Time-Varying Lagged Effects of Negative Affect on Smoking Urges for Subgroups of Nicotine Addiction.Modeling Complexity of EMA Data: Time-Varying Lagged Effects of Negative Affect on Smoking Urges for Subgroups of Nicotine Addiction.Introduction: Ecological momentary asses...