In panel data analysis, individual attributes are of importance in many real applications. With the advancement of data collection, it is often possible to acquire enough information for individual attributes in a collected panel dataset, and data from other individuals may contain the information for the attributes of the individual under concern. Homogeneity pursuit is an important topic in panel data analysis when individual attributes are of interest. Existing approaches are mainly based on either penalized estimation or binary segmentation, and require reasonably large cluster sizes. However, in practice, people often come across panel datasets with small cluster sizes, that is short panel datasets. In this article, we propose a new approach to homogeneity pursuit in panel data analysis, which applies to both long and short panel datasets. Our approach differs from existing methods and enjoys good asymptotic properties that justify its adoption. Extensive simulation studies show that the new approach works very well even when cluster sizes are too small to get any estimators based on one individual, outperforming all alternative methods in all conducted cases. Finally, we apply the new approach to a real dataset and illustrate its practical usefulness and superiority. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.

In panel data analysis, individual attributes are of importance in many real applications. With the advancement of data collection, it is often possible to acquire enough information for individual attributes in a collected panel dataset, and data from other individuals may contain the information for the attributes of the individual under concern. Homogeneity pursuit is an important topic in panel data analysis when individual attributes are of interest. Existing approaches are mainly based on either penalized estimation or binary segmentation, and require reasonably large cluster sizes. However, in practice, people often come across panel datasets with small cluster sizes, that is short panel datasets. In this article, we propose a new approach to homogeneity pursuit in panel data analysis, which applies to both long and short panel datasets. Our approach differs from existing methods and enjoys good asymptotic properties that justify its adoption. Extensive simulation studies show that the new approach works very well even when cluster sizes are too small to get any estimators based on one individual, outperforming all alternative methods in all conducted cases. Finally, we apply the new approach to a real dataset and illustrate its practical usefulness and superiority. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Multiple-use calibration using regression is an important statistical tool. Confidence sets for the x-values associated with all future y-values should guarantee a key property, which can be satisfied by simultaneous tolerance intervals (STI’s), and so multiple-use calibration requires the construction of STI’s. In this article, exact two-sided STI’s have been constructed for polynomial regression over any given covariate interval. There is a misconception that two-sided pointwise tolerance intervals (PTI’s) can be employed for multiple-use calibration. This article shows that the confidence sets based on the two-sided PTI’s do not satisfy the key property and so should not be used. Real-world data examples are given in this article for illustration. Supplementary materials for this article are available online.

Multiple-use calibration using regression is an important statistical tool. Confidence sets for the x-values associated with all future y-values should guarantee a key property, which can be satisfied by simultaneous tolerance intervals (STI’s), and so multiple-use calibration requires the construction of STI’s. In this article, exact two-sided STI’s have been constructed for polynomial regression over any given covariate interval. There is a misconception that two-sided pointwise tolerance intervals (PTI’s) can be employed for multiple-use calibration. This article shows that the confidence sets based on the two-sided PTI’s do not satisfy the key property and so should not be used. Real-world data examples are given in this article for illustration. Supplementary materials for this article are available online.

Multiple-use calibration using regression is an important statistical tool. Confidence sets for the x-values associated with all future y-values should guarantee a key property, which can be satisfied by simultaneous tolerance intervals (STI’s), and so multiple-use calibration requires the construction of STI’s. In this paper, exact two-sided STI’s have been constructed for polynomial regression over any given covariate interval. There is a misconception that two-sided pointwise tolerance intervals (PTI’s) can be employed for multiple-use calibration. This paper shows that the confidence sets based on the two-sided PTI’s do not satisfy the key property and so should not be used. Real-world data examples are given in this paper for illustration.

As a hallmark of COVID-19 progression, lymphopenia alongside its subtle immune disturbance has been widely reported, but yet to be thoroughly elucidated. Aiming at exploring clinical immune biomarkers with accessibility in the current and acute omicron epidemic abrupted in China post-control era, we design a real-world prospective observation cohort in Peking Union Medical College Hospital to describe immunological, haematological profiles inducing lymphocyte subsets related to SARS-CoV-2 infection. In this COVID-19 cohort, we enrolled 17 mild/moderate (M/M), 24 severe (S) and 25 critical (C) patients. The dynamics of lymphocytes of COVID-19 demonstrated that the sharp decline of NK, CD8⁺, and CD4⁺ T cell counts was the main contributor to lymphopenia in the S/C group, compared to the M/M group. Expressions of activation marker CD38 and proliferation marker Ki-67 both in CD8⁺ T and NK cells were significantly higher in all COVID-19 patients than that in healthy donors, independent of disease severity. The subsequent analysis showed in contrast to the M/M group, NK and CD8⁺ T cell counts remained low-level after therapy in the S/C group. CD38 and Ki-67 expressions in NK and CD8⁺ T cells still stay at a high level, despite active treatment. Targeting relatively elderly patients with SARS-CoV-2 infection, severe COVID-19 features the unreversible reduction of NK and CD8⁺ T cells with persistent activation and proliferation, which assist clinicians in early recognizing and saving severe or critical COVID-19 patients. Given that immunophenotype, the new immunotherapy improving NK and CD8⁺ T lymphocyte antiviral efficiency should be considered.

As a hallmark of COVID-19 progression, lymphopenia alongside its subtle immune disturbance has been widely reported, but yet to be thoroughly elucidated. Aiming at exploring clinical immune biomarkers with accessibility in the current and acute omicron epidemic abrupted in China post-control era, we design a real-world prospective observation cohort in Peking Union Medical College Hospital to describe immunological, haematological profiles inducing lymphocyte subsets related to SARS-CoV-2 infection. In this COVID-19 cohort, we enrolled 17 mild/moderate (M/M), 24 severe (S) and 25 critical (C) patients. The dynamics of lymphocytes of COVID-19 demonstrated that the sharp decline of NK, CD8⁺, and CD4⁺ T cell counts was the main contributor to lymphopenia in the S/C group, compared to the M/M group. Expressions of activation marker CD38 and proliferation marker Ki-67 both in CD8⁺ T and NK cells were significantly higher in all COVID-19 patients than that in healthy donors, independent of disease severity. The subsequent analysis showed in contrast to the M/M group, NK and CD8⁺ T cell counts remained low-level after therapy in the S/C group. CD38 and Ki-67 expressions in NK and CD8⁺ T cells still stay at a high level, despite active treatment. Targeting relatively elderly patients with SARS-CoV-2 infection, severe COVID-19 features the unreversible reduction of NK and CD8⁺ T cells with persistent activation and proliferation, which assist clinicians in early recognizing and saving severe or critical COVID-19 patients. Given that immunophenotype, the new immunotherapy improving NK and CD8⁺ T lymphocyte antiviral efficiency should be considered.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.