Mapping an uncertainty zone between interpolated types of a categorical variable

2012 ◽  
Vol 40 ◽  
pp. 146-152 ◽  
Author(s):  
J.K. Yamamoto ◽  
X.M. Mao ◽  
K. Koike ◽  
A.P. Crosta ◽  
P.M.B. Landim ◽  
...  
Keyword(s):  
Categorical Variable ◽  
Uncertainty Zone

scholarly journals A pharmacogenomic approach to the treatment of children with GH deficiency or Turner syndrome

2013 ◽  
Vol 169 (3) ◽  
pp. 277-289 ◽  
Author(s):  
P Clayton ◽  
P Chatelain ◽  
L Tatò ◽  
H W Yoo ◽  
G R Ambler ◽  
...  
Keyword(s):  
Gene Expression ◽  
Turner Syndrome ◽  
Genetic Markers ◽  
Growth Response ◽  
Gh Deficiency ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Continuous Variable ◽  
High Response ◽  
Categorical Variable

ObjectiveIndividual sensitivity to recombinant human GH (r-hGH) is variable. Identification of genetic factors contributing to this variability has potential use for individualization of treatment. The objective of this study was to identify genetic markers and gene expression profiles associated with growth response on r-hGH therapy in treatment-naïve, prepubertal children with GH deficiency (GHD) or Turner syndrome (TS).DesignA prospective, multicenter, international, open-label pharmacogenomic study.MethodsThe associations of genotypes in 103 growth- and metabolism-related genes and baseline gene expression profiles with growth response to r-hGH (cm/year) over the first year were evaluated. Genotype associations were assessed with growth response as a continuous variable and as a categorical variable divided into quartiles.ResultsEleven genes in GHD and ten in TS, with two overlapping between conditions, were significantly associated with growth response either as a continuous variable (seven in GHD, two in TS) or as a categorical variable (four more in GHD, eight more in TS). For example, in GHD, GRB10 was associated with high response (≥Q3; P=0.0012), while SOS2 was associated with low response (≤Q1; P=0.006), while in TS, LHX4 was associated with high response (P=0.0003) and PTPN1 with low response (P=0.0037). Differences in expression were identified for one of the growth response-associated genes in GHD (AKT1) and for two in TS (KRAS and MYOD1).ConclusionsCarriage of specific growth-related genetic markers is associated with growth response in GHD and TS. These findings indicate that pharmacogenomics could have a role in individualized management of childhood growth disorders.

scholarly journals Wrangling categorical data in R

2017 ◽  
Author(s):  
Amelia McNamara ◽  
Nicholas J Horton
Keyword(s):  
Data Quality ◽  
Real World ◽  
Categorical Data ◽  
Data Science ◽  
The Other ◽  
Categorical Variable ◽  
Dynamic Data ◽  
Address Data ◽  
Coding Strategies ◽  
Common Problems

Data wrangling is a critical foundation of data science, and wrangling of categorical data is an important component of this process. However, categorical data can introduce unique issues in data wrangling, particularly in real-world settings with collaborators and periodically-updated dynamic data. This paper discusses common problems arising from categorical variable transformations in R, demonstrates the use of factors, and suggests approaches to address data wrangling challenges. For each problem, we present at least two strategies for management, one in base R and the other from the ‘tidyverse.’ We consider several motivating examples, suggest defensive coding strategies, and outline principles for data wrangling to help ensure data quality and sound analysis.

The Application of Clustering Analysis in Medical Expenses Data Mining

2012 ◽  
Vol 263-266 ◽  
pp. 1987-1990
Author(s):  
Pei Shen ◽  
Ji Kai Zhang ◽  
Hai Ying Hua
Keyword(s):  
Data Mining ◽  
Clustering Analysis ◽  
Categorical Variable ◽  
Pretreatment Method ◽  
Medical Expenses ◽  
Reasonable Result

Find a pretreatment method to transform the continuous dependent variable into categorical variable to get more reasonable result in the medical expenses data mining. As a good pretreatment method of data mining, the clustering analysis shows good applicability.

scholarly journals Centrality of Religiosity as a Resource for Therapy Outcome?

Religions ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 155 ◽  
Author(s):  
Sonja Friedrich-Killinger
Keyword(s):  
Mental Health ◽  
Intervention Study ◽  
Therapy Outcome ◽  
Categorical Variable ◽  
Psychotherapeutic Treatment ◽  
Construct System

The present intervention study tested the following hypothesis: the influence of one’s personal religious construct system is more intense and broader on therapy outcome if it stays central within the personality or becomes more central throughout psychotherapeutic in-treatment. The clinic concept included standard psychotherapy and religious contents. In a pre–post design, participants (N = 208) completed measures of centrality of religiosity and mental health. The hypothesis was tested by treating centrality of religiosity as a categorical variable with reference to a typological distinction. The results indicate that therapy outcome is statistically significantly higher for the groups in which the religious construct system stayed or became more central throughout psychotherapeutic treatment in comparison to the groups with a subordinate position of the religious construct system. These results suggest that the importance and intensity of an individual’s religiosity can play an important role in answering the question of whether religiosity is a resource for improved therapy outcome.

scholarly journals Estimating the Proportion of a Categorical Variable With Probit Regression

2018 ◽  
Vol 49 (3) ◽  
pp. 809-834
Author(s):  
Sergio Martínez ◽  
Maria Rueda ◽  
Antonio Arcos ◽  
Helena Martínez
Keyword(s):  
Auxiliary Information ◽  
Simulated Data ◽  
Real Data ◽  
Probit Model ◽  
Estimation Procedure ◽  
Model Fit ◽  
Categorical Variable ◽  
Probit Regression ◽  
Monte Carlo Experiments ◽  
Regression Estimators

This article discusses the estimation of a population proportion, using the auxiliary information available, which is incorporated into the estimation procedure by a probit model fit. Three probit regression estimators are considered, using model-based and model-assisted approaches. The theoretical properties of the proposed estimators are derived and discussed. Monte Carlo experiments were carried out for simulated data and for real data taken from a database of confirmed dengue cases in Mexico. The probit estimates give valuable results in comparison to alternative estimators. Finally, the proposed methodology is applied to data obtained from an immigration survey.

Dietary Inflammatory Index score and risk of developing endometriosis: A case–control study

2020 ◽  
pp. 228402652096759
Author(s):  
Clarissa Viana Demézio da Silva ◽  
Valéria Lauriana Felipe ◽  
Nitin Shivappa ◽  
James R Hebert ◽  
Jamila Alessandra Perini ◽  
...  
Keyword(s):  
Chronic Pelvic Pain ◽  
Case Control Study ◽  
Dietary Exposure ◽  
Case Control ◽  
Dietary Inflammatory Index ◽  
Categorical Variable ◽  
Food Frequency ◽  
Inflammatory Index ◽  
Multivariable Adjustment ◽  
Control Study

The possible relationship between chronic inflammation from dietary exposure and endometriosis has not been investigated. Thus, the aim of this study was to investigate the association between the Dietary Inflammatory Index (DII®) and endometriosis. Women with endometriotic lesions were defined as cases ( n = 59), and controls ( n = 59) had no visible ectopic endometrium sites. Body mass index (BMI=weight(kg)/height(m)2) was calculated from measured height and weight and waist circumference was measured. A validated semi-quantitative food frequency questionnaire was used to calculate the DII score. Women with endometriosis were younger, thinner; and had a more pro-inflammatory diet and more pain (dysmenorrhea, chronic pelvic pain, deep dyspareunia), than controls. Women with higher DII scores (>0.86) were more likely to have endometriosis and to present with dyspareunia. Results obtained from modeling DII as a categorical variable in relation to risk of endometriosis showed a near tripling of risk (OR = 2.77; 95% CI = 1.13–6.77) for women with DII >0.86 versus those with DII ⩽ 0.86, after adjusting for age and BMI. After multivariable adjustment, women with DII > 0.86 were four times more likely to have endometriosis compared to women with DII ⩽ 0.86 (OR = 4.14; 95% CI= 1.50–11.4). In conclusion, a pro-inflammatory diet was significantly associated with endometriosis.

Is biopsy Gleason sum an independent predictor of biochemical progression following radical prostatectomy after adjusting for the pathological Gleason sum?

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 4652-4652
Author(s):  
N. J. Fitzsimons ◽  
S. Freedland ◽  
J. Presti ◽  
C. Amling ◽  
C. Kane ◽  
...  
Keyword(s):  
Radical Prostatectomy ◽  
Independent Predictor ◽  
Strong Predictor ◽  
Categorical Variable ◽  
Pathological Characteristics ◽  
Improve Model ◽  
Increased Risk ◽  
Psa Failure ◽  
Risk Of Progression ◽  
Biochemical Progression

4652 Background: Biopsy Gleason sum is a known important predictor of PSA failure following radical prostatectomy (RP). However, it is unclear whether it remains predictive of outcome after surgery when the pathological Gleason sum is known. Methods: We determined the association between biopsy Gleason sum and biochemical progression after correcting for both pre-operative and post-operative characteristics including pathological Gleason sum among 1,931 men treated with RP between 1988 and 2005 within the SEARCH Database. Gleason sum was examined as a categorical variable of 2–6, 3+4, and ≥4+3. Results: Higher biopsy Gleason sums were associated with increased prevalence of extra-capsular extension (p < 0.001), positive surgical margins (p < 0.001), seminal vesicle invasion (p < 0.001), positive lymph nodes (p < 0.001), and biochemical progression (log rank, p < 0.001). After adjusting for only pre-operative characteristics, both biopsy Gleason sums of 3+4 (p = 0.004) and ≥4+3 (p < 0.001) were associated with increased risk of biochemical progression when compared to biopsy Gleason sums of 6 or less. After further adjusting for multiple pathological characteristics including pathological Gleason sum, the association between higher biopsy Gleason sum and risk of progression was little changed in that men with biopsy Gleason sums of 3+4 (p = 0.001) and ≥4+3 (p < 0.001) were significantly more likely to progress. Furthermore, when stratified by pathological Gleason sum, higher biopsy Gleason sums were associated with increased risk of biochemical progression within each pathological Gleason sum category (log-rank, p ≤ 0.007). Conclusions: Biopsy Gleason sum remains a strong predictor of outcome even when the pathological Gleason sum is known. If confirmed at other centers, incorporation of biopsy Gleason sum into post-operative nomograms designed to predict risk of progression might improve model precision. No significant financial relationships to disclose.

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