Time to achieving a designated criterion score level: A survival analysis study of test taker performance on the TOEFL iBT® test

2020 ◽  
pp. 026553222094070
Author(s):  
Lora F. Monfils ◽  
Venessa F. Manna
Keyword(s):  
Survival Analysis ◽  
Cox Regression ◽  
Test Taker ◽  
Background Characteristics ◽  
Repeated Testing ◽  
Criterion Score ◽  
Testing Occasion ◽  
The Common ◽  
Toefl Ibt ◽  
Total Test

This study used survival analysis to examine the patterns and factors associated with time to achieving designated score criteria on a test of English as a foreign language. This was modeled using an extension of the Cox regression model, with two criterion score levels defined as achieving a TOEFL iBT® total test scale score at or above the Common European Framework of Reference (CEFR) Level B2 and at Level C1, respectively. Factors included in the model were test taker background characteristics including age, gender, native language type, exposure to English, and reason for testing. Additionally, to account for those who tested more than once within the study period, and thus had multiple records, an indicator for order of testing occasion was included in the model. Results indicate that approximately 82% of the test takers in our study sample tested one time in the study period (2014–2016), and the number of repeaters decreased rapidly across occasions. For those who did not achieve the designated criterion scores at first testing, the likelihood of achievement increases with repeated testing, with a somewhat greater effect for the less stringent B2 criterion. Results also indicate that the association of gender with performance differed across levels.

scholarly journals Testing the proportional hazards assumption in cox regression and dealing with possible non-proportionality in total joint arthroplasty research: methodological perspectives and review

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ilari Kuitunen ◽  
Ville T. Ponkilainen ◽  
Mikko M. Uimonen ◽  
Antti Eskelinen ◽  
Aleksi Reito
Keyword(s):  
Survival Analysis ◽  
Regression Model ◽  
Total Joint Arthroplasty ◽  
Full Text ◽  
Proportional Hazards ◽  
Cox Regression ◽  
Joint Arthroplasty ◽  
Central Research ◽  
Cox Regression Model ◽  
Pubmed Database

Abstract Background Survival analysis and effect of covariates on survival time is a central research interest. Cox proportional hazards regression remains as a gold standard in the survival analysis. The Cox model relies on the assumption of proportional hazards (PH) across different covariates. PH assumptions should be assessed and handled if violated. Our aim was to investigate the reporting of the Cox regression model details and testing of the PH assumption in survival analysis in total joint arthroplasty (TJA) studies. Methods We conducted a review in the PubMed database on 28th August 2019. A total of 1154 studies were identified. The abstracts of these studies were screened for words “cox and “hazard*” and if either was found the abstract was read. The abstract had to fulfill the following criteria to be included in the full-text phase: topic was knee or hip TJA surgery; survival analysis was used, and hazard ratio reported. If all the presented criteria were met, the full-text version of the article was then read. The full-text was included if Cox method was used to analyze TJA survival. After accessing the full-texts 318 articles were included in final analysis. Results The PH assumption was mentioned in 114 of the included studies (36%). KM analysis was used in 281 (88%) studies and the KM curves were presented graphically in 243 of these (87%). In 110 (45%) studies, the KM survival curves crossed in at least one of the presented figures. The most common way to test the PH assumption was to inspect the log-minus-log plots (n = 59). The time-axis division method was the most used corrected model (n = 30) in cox analysis. Of the 318 included studies only 63 (20%) met the following criteria: PH assumption mentioned, PH assumption tested, testing method of the PH assumption named, the result of the testing mentioned, and the Cox regression model corrected, if required. Conclusions Reporting and testing of the PH assumption and dealing with non-proportionality in hip and knee TJA studies was limited. More awareness and education regarding the assumptions behind the used statistical models among researchers, reviewers and editors are needed to improve the quality of TJA research. This could be achieved by better collaboration with methodologists and statisticians and introducing more specific reporting guidelines for TJA studies. Neglecting obvious non-proportionality undermines the overall research efforts since causes of non-proportionality, such as possible underlying pathomechanisms, are not considered and discussed.

scholarly journals Cox regression survival analysis with compositional covariates: Application to modelling mortality risk from 24-h physical activity patterns

2019 ◽  
Vol 29 (5) ◽  
pp. 1447-1465 ◽  
Author(s):  
DE McGregor ◽  
J Palarea-Albaladejo ◽  
PM Dall ◽  
K Hron ◽  
SFM Chastin
Keyword(s):  
Public Health ◽  
Physical Activity ◽  
Survival Analysis ◽  
Regression Model ◽  
Cox Regression ◽  
Public Health Problem ◽  
Sitting Time ◽  
Cox Regression Model ◽  
Log Ratio ◽  
Activity Behaviour

Survival analysis is commonly conducted in medical and public health research to assess the association of an exposure or intervention with a hard end outcome such as mortality. The Cox (proportional hazards) regression model is probably the most popular statistical tool used in this context. However, when the exposure includes compositional covariables (that is, variables representing a relative makeup such as a nutritional or physical activity behaviour composition), some basic assumptions of the Cox regression model and associated significance tests are violated. Compositional variables involve an intrinsic interplay between one another which precludes results and conclusions based on considering them in isolation as is ordinarily done. In this work, we introduce a formulation of the Cox regression model in terms of log-ratio coordinates which suitably deals with the constraints of compositional covariates, facilitates the use of common statistical inference methods, and allows for scientifically meaningful interpretations. We illustrate its practical application to a public health problem: the estimation of the mortality hazard associated with the composition of daily activity behaviour (physical activity, sitting time and sleep) using data from the U.S. National Health and Nutrition Examination Survey (NHANES).

scholarly journals Constructing the Logical Regression Model to Predict the Target of Jianpi Jiedu Decoction in the Treatment of Hepatocellular Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Rongjie Zhang ◽  
Yan Chen ◽  
Ge Zhou ◽  
Baoguo Sun ◽  
Yue Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Survival Analysis ◽  
Regression Model ◽  
Target Genes ◽  
Cox Regression ◽  
Risk Group ◽  
Cox Regression Analysis ◽  
Expression Levels ◽  
Prognostic Analysis ◽  
Significant Difference

Objectives. The purpose of this study was to identify the molecular mechanism and prognosis-related genes of Jianpi Jiedu decoction in the treatment of hepatocellular carcinoma. Methods. The gene expression data of hepatocellular carcinoma samples and normal tissue samples were downloaded from TCGA database, and the potential targets of drug composition of Jianpi Jiedu decoction were obtained from TCMSP database. The genes were screened out in order to obtain the expression of these target genes in patients with hepatocellular carcinoma. The differential expression of target genes was analyzed by R software, and the genes related to prognosis were screened by univariate Cox regression analysis. Then, the LASSO model was constructed for risk assessment and survival analysis between different risk groups. At the same time, independent prognostic analysis, GSEA analysis, and prognostic analysis of single gene in patients with hepatocellular carcinoma were performed. Results. 174 compounds of traditional Chinese medicine were screened by TCMSP database, corresponding to 122 potential targets. 39 upregulated genes and 9 downregulated genes were screened out. A total of 20 candidate prognostic related genes were screened out by univariate Cox analysis, of which 12 prognostic genes were involved in the construction of the LASSO regression model. There was a significant difference in survival time between the high-risk group and low-risk group ( p < 0.05 ). Among the genes related to prognosis, the expression levels of CCNB1, NQO1, NUF2, and CHEK1 were high in tumor tissues ( p < 0.05 ). Survival analysis showed that the high expression levels of these four genes were significantly correlated with poor prognosis of HCC ( p < 0.05 ). GSEA analysis showed that the main KEGG enrichment pathways were lysine degradation, folate carbon pool, citrate cycle, and transcription factors. Conclusions. In the study, we found that therapy target genes of Jianpi Jiedu decoction were mainly involved in metabolism and apoptosis in hepatocellular carcinoma, and there was a close relationship between the prognosis of hepatocellular carcinoma and the genes of CCNB1, NQO1, NUF2, and CHEK1.

scholarly journals Identification of Immune-Related Prognostic mRNA and lncRNA in Patients with Hepatocellular Carcinoma

2022 ◽  
Vol 2022 ◽  
pp. 1-16
Author(s):  
Dan Chen ◽  
Xiaoting Li ◽  
Hui Li ◽  
Kai Wang ◽  
Xianghua Tian
Keyword(s):  
Hepatocellular Carcinoma ◽  
Flow Cytometry ◽  
T Cells ◽  
Regression Analysis ◽  
Survival Analysis ◽  
Immune Cells ◽  
Cox Regression ◽  
Differentially Expressed ◽  
Cox Regression Analysis ◽  
Immune Related Genes

Background. As the most common hepatic malignancy, hepatocellular carcinoma (HCC) has a high incidence; therefore, in this paper, the immune-related genes were sought as biomarkers in liver cancer. Methods. In this study, a differential expression analysis of lncRNA and mRNA in The Cancer Genome Atlas (TCGA) dataset between the HCC group and the normal control group was performed. Enrichment analysis was used to screen immune-related differentially expressed genes. Cox regression analysis and survival analysis were used to determine prognostic genes of HCC, whose expression was detected by molecular experiments. Finally, important immune cells were identified by immune cell infiltration and detected by flow cytometry. Results. Compared with the normal group, 1613 differentially expressed mRNAs (DEmRs) and 1237 differentially expressed lncRNAs (DElncRs) were found in HCC. Among them, 143 immune-related DEmRs and 39 immune-related DElncRs were screened out. These genes were mainly related to MAPK cascade, PI3K-AKT signaling pathway, and TGF-beta. Through Cox regression analysis and survival analysis, MMP9, SPP1, HAGLR, LINC02202, and RP11-598F7.3 were finally determined as the potential diagnostic biomarkers for HCC. The gene expression was verified by RT-qPCR and western blot. In addition, CD4 + memory resting T cells and CD8 + T cells were identified as protective factors for overall survival of HCC, and they were found highly expressed in HCC through flow cytometry. Conclusion. The study explored the dysregulation mechanism and potential biomarkers of immune-related genes and further identified the influence of immune cells on the prognosis of HCC, providing a theoretical basis for the prognosis prediction and immunotherapy in HCC patients.

scholarly journals Survival Analysis and Determinants of The First Birth Interval in Indonesia

CAUCHY ◽  
2018 ◽  
Vol 5 (2) ◽  
pp. 55
Author(s):  
Alfensi Faruk ◽  
Endro Setyo Cahyono ◽  
Ning Eliyati
Keyword(s):  
Survival Analysis ◽  
Educational Level ◽  
Birth Interval ◽  
Cox Regression ◽  
Wealth Index ◽  
First Birth ◽  
Factors Affecting ◽  
Kaplan Meier ◽  
Censored Observations ◽  
Socioeconomic And Demographic Factors

<p class="Abstract">The first birth interval is one of the indicators of women’s fertility rate. Because in most cases the first birth interval contains censored observations, the only appropriate statistical method to handle such data is survival analysis. The main objective of this study is to analyze several socioeconomic and demographic factors that affect the first birth interval in Indonesia using the univariate and multivariate survival analysis, that is Kaplan-Meier method and Cox regression model, respectively. The sample is obtained from 2012 Indonesian Demographic and Health Survey (IDHS) and consists of 28242 ever married women aged 15-49 at the time of interview. The results show that age at the first birth, women's educational level, husband’s educational level, contraceptive knowledge, wealth index, and employment status are the significant factors affecting the first birth interval in Indonesia.</p>

scholarly journals Identification and Validation of a Prognostic 5-Protein Signature for Biochemical Recurrence Following Radical Prostatectomy for Prostate Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Daojun Lv ◽  
Zanfeng Cao ◽  
Wenjie Li ◽  
Haige Zheng ◽  
Xiangkun Wu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Survival Analysis ◽  
Biochemical Recurrence ◽  
Cox Regression ◽  
Characteristic Curve ◽  
The Cancer Genome Atlas ◽  
Medical Decision ◽  
Regression Analyses ◽  
Cox Regression Analysis ◽  
Protein Signature

Background: Biochemical recurrence (BCR) is an indicator of prostate cancer (PCa)-specific recurrence and mortality. However, there is a lack of an effective prediction model that can be used to predict prognosis and to determine the optimal method of treatment for patients with BCR. Hence, the aim of this study was to construct a protein-based nomogram that could predict BCR in PCa.Methods: Protein expression data of PCa patients was obtained from The Cancer Proteome Atlas (TCPA) database. Clinical data on the patients was downloaded from The Cancer Genome Atlas (TCGA) database. Lasso and Cox regression analyses were conducted to select the most significant prognostic proteins and formulate a protein signature that could predict BCR. Subsequently, Kaplan–Meier survival analysis and Cox regression analyses were conducted to evaluate the performance of the prognostic protein-based signature. Additionally, a nomogram was constructed using multivariate Cox regression analysis.Results: We constructed a 5-protein-based prognostic prediction signature that could be used to identify high-risk and low-risk groups of PCa patients. The survival analysis demonstrated that patients with a higher BCR showed significantly worse survival than those with a lower BCR (p &lt; 0.0001). The time-dependent receiver operating characteristic curve showed that the signature had an excellent prognostic efficiency for 1, 3, and 5-year BCR (area under curve in training set: 0.691, 0.797, 0.808 and 0.74, 0.739, 0.82 in the test set). Univariate and multivariate analyses indicated that this 5-protein signature could be used as independent prognosis marker for PCa patients. Moreover, the concordance index (C-index) confirmed the predictive value of this 5-protein signature in 3, 5, and 10-year BCR overall survival (C-index: 0.764, 95% confidence interval: 0.701–0.827). Finally, we constructed a nomogram to predict BCR of PCa.Conclusions: Our study identified a 5-protein-based signature and constructed a nomogram that could reliably predict BCR. The findings might be of paramount importance for the prediction of PCa prognosis and medical decision-making.Subjects: Bioinformatics, oncology, urology.

An overview on standard statistical methods for assessing exposure-outcome link in survival analysis (Part II): the Kaplan-Meier analysis and the Cox regression method

2012 ◽  
Vol 24 (3) ◽  
pp. 203-206 ◽  
Author(s):  
Samar Abd ElHafeez ◽  
Claudia Torino ◽  
Graziella D’Arrigo ◽  
Davide Bolignano ◽  
Fabio Provenzano ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Statistical Methods ◽  
Cox Regression ◽  
Regression Method ◽  
Kaplan Meier

Factors Influencing the Lifetime of Telecommunication and Information Technology Standards

2010 ◽  
pp. 242-259
Author(s):  
Knut Blind
Keyword(s):  
Survival Analysis ◽  
New Technologies ◽  
Cox Regression ◽  
Medical Science ◽  
International Standards ◽  
Control Mechanisms ◽  
Survival Times ◽  
Scientific Publications ◽  
The One ◽  
Standard Documents

Besides these very conceptual or theoretical approaches to deal with standards dynamics, several case study analyses exist, which focus on the standard maintenance and succession (Egyedi, Loeffen 2002) in order to answer the question how to deal with heritage relations between standards and on standard integrity (Egyedi, Hudson 2005) and in order to discuss control mechanisms that safeguard the integrity of (de facto) standards. This paper adds an additional methodological dimension to the analysis of the dynamics of standards by a strong focus on the life times of standards. The contribution of this paper to the emerging research on the dynamics of standards is twofold. First, the descriptive presentation of life times of standards focusing both on average publication years and survival times reflects on the one hand the historical development of ICT over time and on the other hand its dynamics in the various subfields. So far other indicators like scientific publications or patent applications are used to describe the development especially of new technologies, e. g. biotechnology or nanotechnology. The analysis of publications of standard documents extends the former exercises by a new more market and diffusion related dimension. Second, the characteristics of standard documents are used to explain their life times. Here we borrow for the first time general approaches from bibliometrics and patent analysis in order to explain life times of standards as indicator for their value by documents’ characteristics. The remainder of the paper is structured as follows. First, we analyse the average lifetimes of standards in a quantitative manner, taking into account differences between countries. Since the simple approach of calculating the average lifetimes of historical standards does not allow us to include standards which are still alive, we have to apply a more sophisticated methodology, the so-called survival analysis, which was initially mainly applied in medical science. The application of this statistical approach produces average lifetimes of standards, taking into account the expected lifetime of standards which are still valid. This approach is crucial, especially for the analysis of ICT standards, because the number of valid standards relative to historical standards is rather high. Due to the very high relevance of international standards in the ICT sector and the high quality of this subsample, we concentrate the survival analysis espeically on the international standards including the standards released by the European standardisation bodies. The results of this analysis provide us with new insights about the expected lifetimes of standards differentiated by technology in the ICT area. The final step of our analysis tries to answer the question which causal factors influence the lifetimes of standards in the ICT sector. We present first insights by applying the so-called Cox regression, which allows us to identify whether some selected characteristics of a standard, like cross references or references to international standards, have a significant impact on its actual or expected lifetime. The approach to assess the importance of a technical document by analysing its references to other documents or being referenced in other documents has a long tradition in evaluating the value of patents by counting and analysing their citations. The paper concludes with a brief summary of the main results, but also with some general recommendations regarding standardisation processes and the maintenance of standards derived from the new insights.

scholarly journals Co-Expression of Coxsackievirus/Adenovirus Receptors and Desmoglein 2 in Lung Adenocarcinoma: A Comprehensive Analysis of Bioinformatics and Tissue Microarrays

2020 ◽  
Vol 9 (11) ◽  
pp. 3693
Author(s):  
Ching-Fu Weng ◽  
Chi-Jung Huang ◽  
Mei-Hsuan Wu ◽  
Henry Hsin-Chung Lee ◽  
Thai-Yen Ling
Keyword(s):  
Overall Survival ◽  
Survival Analysis ◽  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Epithelial Mesenchymal Transition ◽  
Early Stage ◽  
The Cancer Genome Atlas ◽  
Cancer Tissue ◽  
Mesenchymal Transition ◽  
Kaplan Meier

Introduction: Coxsackievirus/adenovirus receptors (CARs) and desmoglein-2 (DSG2) are similar molecules to adenovirus-based vectors in the cell membrane. They have been found to be associated with lung epithelial cell tumorigenesis and can be useful markers in predicting survival outcome in lung adenocarcinoma (LUAD). Methods: A gene ontology enrichment analysis disclosed that DSG2 was highly correlated with CAR. Survival analysis was then performed on 262 samples from the Cancer Genome Atlas, forming “Stage 1A” or “Stage 1B”. We therefore analyzed a tissue microarray (TMA) comprised of 108 lung samples and an immunohistochemical assay. Computer counting software was used to calculate the H-score of the immune intensity. Cox regression and Kaplan–Meier analyses were used to determine the prognostic value. Results: CAR and DSG2 genes are highly co-expressed in early stage LUAD and associated with significantly poorer survival (p = 0.0046). TMA also showed that CAR/DSG2 expressions were altered in lung cancer tissue. CAR in the TMA was correlated with proliferation, apoptosis, and epithelial–mesenchymal transition (EMT), while DSG2 was associated with proliferation only. The Kaplan–Meier survival analysis revealed that CAR, DSG2, or a co-expression of CAR/DSG2 was associated with poorer overall survival. Conclusions: The co-expression of CAR/DSG2 predicted a worse overall survival in LUAD. CAR combined with DSG2 expression can predict prognosis.

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