Results 111 to 120 of about 1,718,863 (277)
The treatment of missing data on placement tools for predicting success in college algebra at the University of Alaska [PDF]
Master's Project (M.S.) University of Alaska Fairbanks, 2014This project investigated the statistical significance of baccalaureate student placement tools such as tests scores and completion of a developmental course on predicting success in a college ...
Crawford, Alyssa
core
Interrogating the immune landscape of microsatellite stable RAS‐mutated colon cancer
COLOSSUS project RAS‐mutated MSS colon cancer study explored transcriptomics and immune cell density by immunohistochemistry (IHC), Immunoscore (IS), ISIC/TuLIS scores, mutation counts, and detected different prevalences but similar microenvironment composition across immune markers with clinical relevance for future immunotherapy combination ...
Rodrigo Dienstmann +61 more
wiley +1 more source
PERBANDINGAN MEKANISME DATA HILANG PADA MODEL NORMAL [PDF]
Data hilang merupakan sutu fenomena yang umum terjadi dalam penelitian survei atau experimental, berdasarkan fakta tersebut berbagai metode statistika dikembangkan untuk mengatasinya.
Yadi, Suprijadi, Zulhanif, Zulhanif
core
Evolutionary Spectrum for Random Field and Missing Observations [PDF]
There are innumerable situations where the data observed from a non-stationary random field are collected with missing values. In this work a consistent estimate of the evolutionary spectral density is given where some observations are randomly missing.
openaire +2 more sources
Keratin 19 (KRT19) is overexpressed in high‐grade serous ovarian cancer with high levels of Kallikrein‐related peptidases (KLK) 4–7 and is associated with poor survival. In vivo analyses demonstrate that elevated KRT19 increases peritoneal tumour burden.
Sophia Bielesch +13 more
wiley +1 more source
Model-based clustering with missing not at random data
Model-based unsupervised learning, as any learning task, stalls as soon as missing data occurs. This is even more true when the missing data are informative, or said missing not at random (MNAR). In this paper, we propose model-based clustering algorithms designed to handle very general types of missing data, including MNAR data. To do so, we introduce
Sportisse, Aude +6 more
openaire +5 more sources
Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova +14 more
wiley +1 more source
Trial arm outcome variance difference after dropout as an indicator of missing-not-at-random bias in randomized controlled trials. [PDF]
Hazewinkel AD +3 more
europepmc +1 more source
Missing data imputation using classification and regression trees [PDF]
Background Missing data are common when analyzing real data. One popular solution is to impute missing data so that one complete dataset can be obtained for subsequent data analysis.
Cheng-Yang Chen, Yu-Wei Chang
doaj +2 more sources
Beyond its role in immune evasion, this study identified that CD47 drives tumor‐intrinsic signaling in non‐small cell lung cancer (NSCLC). Transcriptomic profiling and functional studies revealed that CD47 regulates cell adhesion, migration, and metastasis through an ERK–EMT signaling axis.
Asa P.Y. Lau +8 more
wiley +1 more source

