scholarly journals Sign test of independence between two random vectors

2003 ◽  
Vol 62 (1) ◽  
pp. 9-21 ◽  
Author(s):  
Sara Taskinen ◽  
Annaliisa Kankainen ◽  
Hannu Oja
Keyword(s):  
Sign Test ◽  
Random Vectors ◽  
Test Of Independence

Pengaruh Self Help Group Terhadap Kemampuan Keluarga Dalam Merawat Klien Skizofrenia Di Poli Jiwa Puskesmas Kalitidu

2020 ◽  
Vol 10 (2) ◽  
Author(s):  
Yusuf Efendi ◽  
Errix Kristian Julianto
Keyword(s):  
Mental Disorders ◽  
Group Intervention ◽  
Family Members ◽  
Wilcoxon Test ◽  
Sign Test ◽  
Significance Level ◽  
Self Help ◽  
Before And After ◽  
Self Help Groups ◽  
Self Help Group

ABSTRAKDiera perkembangan jaman saat ini, beberapa keluarga dihadapkan dengan permasalahna tentang adanya angggota keluarga yeng mengaami gangguan jiwa, tak jarang keluarga tidak mengetahui bagaimana merawat angota keluarga dengan gangguan jiwa. Self help group pada keluarga dengan gangguan jiwa perlu dilakukan untuk membantu keluarga mengatasi permasalahannya yang diselesaikan bersama dalam kelompok. Manfaat yang didapatkan pada terapi ini adalah terdapatnya peningkatan pengetahuan keluarga tentang Skizofrenia. Peningkatan pengetahuan ini akan berdampak terhadap kemampuan keluarga dalam merawat klien Skizofrenia..Desain penelitian ini menggunakan desain pre eksperimental dengan rancangan one group pre-posttest design. Sampel pada penelitian ini adalah keluarga penderita Skizofrenia di PKU Jiwa Kalitidu yang berjumlah 32. . Data dikumpulkan menggunakan kuesioner kemudian dianalisis dengan menggunakan uji Wolcoxon sign dengan tingkat kemaknaan 0,05. Hasil penelitian menunjukkan bahwa kondisi responden sebelum dan sesudah dilakukan intervensi dengan self help group pada kemampuan merawat dengan  nilai uji wilcoxon sebesar 0,001 yang berarti ada pengaruh dari intervensi self help group dengan merawat keluarga dengan gangguan jiwa. Kata Kunci       : Self Help Group, Kemampuan Merawat, Skizofrenia   ABSTRACT. In the current era of development, some families are faced with problems about family members who suffer from mental disorders, often families do not know how to care for family members with mental disorders. Self help groups for families with mental disorders need to be done to help families overcome the problems that are solved together in a group. The benefit of this therapy is that there is an increase in family knowledge about Schizophrenia. This increase in knowledge will have an impact on the ability of families to care for Schizophrenia clients.The design of this study used a pre-experimental design with one group pre-posttest design. The sample in this study was the families of Schizophrenics in  Kalitidu public helath centre, amounting to 32.. Data were collected using a questionnaire and then analyzed using the Wolcoxon sign test with a significance level of 0.05.The results showed that the condition of the respondents before and after the intervention with self help group on the ability to care for Wilcoxon test value of 0.001, which means there is an influence of self help group intervention by caring for families with mental disorders. Keywords: Self Help Group, Caring Ability, Schizophrenia

Altmetrics of COVID-19 research: An analysis of study dissemination by Twitter compared to citation rates (Preprint)

2020 ◽  
Author(s):  
Nicholas Fabiano ◽  
Zachary Hallgrimson ◽  
Sakib Kazi ◽  
Jean-Paul Salameh ◽  
Stanley Wong ◽  
...  
Keyword(s):  
Social Media ◽  
Case Report ◽  
Open Access ◽  
South America ◽  
Negative Binomial ◽  
Citation Rate ◽  
Sign Test ◽  
Study Characteristics ◽  
Journal Impact ◽  
Epidemic Forecasting

BACKGROUND The COVID-19 pandemic has resulted in over 1,000,000 cases across 181 countries worldwide. The global impact of COVID-19 has resulted in a surge of related research. Researchers have turned to social media platforms, namely Twitter, to disseminate their studies. The online database Altmetric is a tool which tracks the social media metrics of articles and is complementary to traditional, citation-based metrics. Citation-based metrics may fail to portray dissemination accurately, due to the lengthy publication process. Altmetrics are not subject to this time-lag, suggesting that they may be an effective marker of research dissemination during the COVID-19 pandemic. OBJECTIVE To assess the dissemination of COVID-19 research articles as measured by Twitter dissemination, compared to traditional citation-based metrics, and determine study characteristics associated with tweet rates. METHODS COVID-19 studies obtained from LitCovid published between January 1st to March 18th, 2020 were screened for inclusion. The following study characteristics were extracted independently, in single: Topic (General Info, Mechanism, Diagnosis, Transmission, Treatment, Prevention, Case Report, and Epidemic Forecasting), open access status (open access and subscription-based), continent of corresponding author (Asia, Australia, Africa, North America, South America, and Europe), tweets, and citations. A sign test was used to compare the tweet rate and citation rate per day. A negative binomial regression analysis was conducted to evaluate the association between tweet rate and study characteristics of interest. RESULTS 1328 studies were included in the analysis. Tweet rates were found to be significantly higher than citation rates for COVID-19 studies, with a median tweet rate of 1.09 (SD 156.95) tweets per day and median citation rate of 0.00 (SD 3.02) citations per day, resulting in a median of differences of 1.09 (95% CI 0.86-1.33, P < .001). 2018 journal impact factors were positively correlated with tweet rate (P < .001). The topics Diagnosis (P = .01), Transmission (P < .001), Treatment (P = .01), and Epidemic Forecasting (P < 0.001) were positively correlated with tweet rate, relative to Case Report. The following continents of the corresponding author were negatively correlated with tweet rate, Africa (P <.001), Australia (P = .03), and South America (P < .001), relative to Asia. Open access journals were negatively correlated with tweet rate, relative to subscription-based journals (P < .001). CONCLUSIONS COVID-19 studies had significantly higher tweets rates compared to citation rates. This study further identified study characteristics that are correlated with the dissemination of studies on Twitter, such as 2018 journal impact factor, continent of the corresponding author, topic of study, and open access status. This highlights the importance of altmetrics in periods of rapidly expanding research, such as the COVID-19 pandemic to localize highly disseminated articles.

scholarly journals Orr's Quantitative Trait Loci Sign Test Under Conditions of Trait Ascertainment

Genetics ◽  
2003 ◽  
Vol 165 (1) ◽  
pp. 445-446 ◽  
Author(s):  
Eric C Anderson ◽  
Montgomery Slatkin
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Sign Test ◽  
Trait Loci

scholarly journals A kernel log-rank test of independence for right-censored data

2021 ◽  
pp. 1-26
Author(s):  
Tamara Fernández ◽  
Arthur Gretton ◽  
David Rindt ◽  
Dino Sejdinovic
Keyword(s):  
Censored Data ◽  
Rank Test ◽  
Right Censored Data ◽  
Test Of Independence ◽  
Log Rank Test

scholarly journals On Randomized Trace Estimates for Indefinite Matrices with an Application to Determinants

2021 ◽  
Author(s):  
Alice Cortinovis ◽  
Daniel Kressner
Keyword(s):  
Large Scale ◽  
Gaussian Process Regression ◽  
Likelihood Estimation ◽  
Random Vectors ◽  
Symmetric Positive Definite ◽  
Matrix Logarithm ◽  
The Matrix ◽  
Trace Estimation ◽  
Scale Matrix ◽  
Existing Result

AbstractRandomized trace estimation is a popular and well-studied technique that approximates the trace of a large-scale matrix B by computing the average of $$x^T Bx$$ x T B x for many samples of a random vector X. Often, B is symmetric positive definite (SPD) but a number of applications give rise to indefinite B. Most notably, this is the case for log-determinant estimation, a task that features prominently in statistical learning, for instance in maximum likelihood estimation for Gaussian process regression. The analysis of randomized trace estimates, including tail bounds, has mostly focused on the SPD case. In this work, we derive new tail bounds for randomized trace estimates applied to indefinite B with Rademacher or Gaussian random vectors. These bounds significantly improve existing results for indefinite B, reducing the number of required samples by a factor n or even more, where n is the size of B. Even for an SPD matrix, our work improves an existing result by Roosta-Khorasani and Ascher (Found Comput Math, 15(5):1187–1212, 2015) for Rademacher vectors. This work also analyzes the combination of randomized trace estimates with the Lanczos method for approximating the trace of f(B). Particular attention is paid to the matrix logarithm, which is needed for log-determinant estimation. We improve and extend an existing result, to not only cover Rademacher but also Gaussian random vectors.

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