نتایج جستجو برای: مکانیسم گمشدن کاملاً تصادفی (MCAR)

تعداد نتایج: 121067  

مدل‌یابی معادلات ساختاری، یک رویکرد آماری چندمتغیری نیرومند جهت ارزیابی روابط پیچیده‌ی بین متغیرهای مکنون در بسیاری از حوزه‌های علوم انسانی و رفتاری است. یکی از چالش‌های رایج در برآورد مدل‌های معادلات ساختاری که بر مبنای آزمون فرضیه‌ها انجام می‌شود، وجود داده‌های گمشده است. شیوه‌ی معمول، حذف آزمودنی‌هایی با پاسخ‌های گمشده روی هر کدام از سوالات است که با افزایش درصد مقادیر گمشده در مجموعه داده‌ه...

Journal: : 2023

هدف: در آویشن، تیمول و کارواکرول به‫دلیل برخورداری از خواص درمانی متنوعی نظیر ضد تومور مورد توجه فارماکولوژیست­ها قرار گرفته­اند. تاکنون، طیف تیمارها مثل الیسیتورها برای افزایش محتوی پیشنهاد شده­اند. این پژوهش نیز با هدف ارزیابی اثر هم­افزائی اشعه UV-A متیل‌جاسمونات بر بیوسنتز صورت گرفت.مواد روش­ها: بذور آویشن آزمایش فاکتوریل زمان طرح کاملا تصادفی سه تکرار تحت شرایط گلخانه­ای گلدان­های پلاستیکی...

Journal: :Molecular pharmacology 2002
Akiko Ueda Satoru Kakizaki Masahiko Negishi Tatsuya Sueyoshi

Steroid hormones modulate activity of the nuclear receptor constitutive active receptor (CAR, or constitutive androstane receptor) in mouse liver. Progesterone and testosterone repress the constitutive activity of mouse CAR (mCAR) in cell-mediated transfection assays, whereas estrogens activate the repressed receptor. This repression and activation is not observed with human CAR. To define the ...

Journal: :Molecular vision 2002
Xuemei Zhu Aimin Li Bruce Brown Ellen R Weiss Shoji Osawa Cheryl M Craft

PURPOSE Arrestins are a superfamily of regulatory proteins that down-regulate activated and phosphorylated G-protein coupled receptors (GPCRs). Cone arrestin (CAR) is expressed in cone photoreceptors and pinealocytes and may contribute to the shutoff mechanisms associtated with high acuity color vision. To initiate a study of CAR's function in cone phototransduction, the mouse CAR (mCAR) transc...

Journal: :Epidemiology 2020

2005
Conor Dolan Sophie van der Sluis Raoul Grasman

We consider power calculation in structural equation modeling with data missing completely at random (MCAR). Muthén and Muthén (2002) recently demonstrated how power calculations with data MCAR can be carried out by means of a Monte Carlo study. Here we show that the method of Satorra and Saris (1985), which is based on the nonnull distribution of the (normal theory) log-likelihood ratio test, ...

Journal: :IEEE transactions on pattern analysis and machine intelligence 2017
Ching-Hui Chen Vishal M. Patel Rama Chellappa

Learning a classifier from ambiguously labeled face images is challenging since training images are not always explicitly-labeled. For instance, face images of two persons in a news photo are not explicitly labeled by their names in the caption. We propose a Matrix Completion for Ambiguity Resolution (MCar) method for predicting the actual labels from ambiguously labeled images. This step is fo...

Journal: :The annals of applied statistics 2009
Yufen Zhang James S Hodges Sudipto Banerjee

Rapid developments in geographical information systems (GIS) continue to generate interest in analyzing complex spatial datasets. One area of activity is in creating smoothed disease maps to describe the geographic variation of disease and generate hypotheses for apparent differences in risk. With multiple diseases, a multivariate conditionally autoregressive (MCAR) model is often used to smoot...

Journal: :Molecular pharmacology 2006
F Hosseinpour R Moore M Negishi T Sueyoshi

The constitutive active receptor (CAR) in mouse primary hepatocytes undergoes okadaic acid (OA)-sensitive nuclear translocation after activation by xenobiotics such as phenobarbital (PB) and 1,4 bis[2-(3,5-dichloropyridyloxy)]benzene (TCPOBOP). We have now mimicked this TCPOBOP-dependent and OA-sensitive translocation of mouse CAR (mCAR) in HepG2 cells and have demonstrated that protein phospha...

2014
Xiaoping Zhu

Missing data can frequently occur in a longitudinal data analysis. In the literature, many methods have been proposed to handle such an issue. Complete case (CC), mean substitution (MS), last observation carried forward (LOCF), and multiple imputation (MI) are the four most frequently used methods in practice. In a real-world data analysis, the missing data can be MCAR, MAR, or MNAR depending o...

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