scholarly journals Can An Algebraic Diagnostic Test be Used to Predict Final Grades in an Introductory Statistics Class?

2015 ◽  
Vol 12 (2) ◽  
Author(s):  
Justine Kirksey ◽  
Anthony Cooper
Keyword(s):  
Logistic Regression ◽  
Linear Regression ◽  
Diagnostic Test ◽  
California State University ◽  
Introductory Statistics ◽  
State University ◽  
Passing Rates ◽  
Statistics Course ◽  
Final Grades ◽  
Algebraic Test

The Department of Mathematics and Statistics at California State University Sacramento has been using the Intermediate Algebra Diagnostic (IAD) test as a proxy tool to screen students intending to enroll in an introductory statistics course (Stat 1). However, the use of an algebraic test as a diagnostic tool for a statistics course has been questioned by some faculty members and students at this university. The regression models used in this study (simple linear regression, hierarchical linear regression, and logistic regression) show that higher IAD scores are related to higher final grades in Stat 1, even after adjusting for different instructors. Inferences were also made in this study to predict a passing grade and passing rates in Stat 1 based on the bounds of the confidence and prediction intervals obtained for the IAD scores with these models. KEYWORDS: Linear Regression, Logistic Regression, Statistics Diagnostic Test, Algebra Diagnostic Test, MDTP, Introductory Statistics

Statistical literacy and the news media

2017 ◽  
Author(s):  
Andrew Gelman ◽  
Deborah Nolan
Keyword(s):  
News Media ◽  
News Article ◽  
Introductory Statistics ◽  
News Story ◽  
Statistical Literacy ◽  
Process Information ◽  
Statistics Course ◽  
Reported Study ◽  
Original Report

An important theme in an introductory statistics course is the connection between statistics and the outside world. Described in this chapter are assignments that can be useful in getting students to learn how to gather and process information presented in the news and scientific reports. These assignments seem to work well only when students have direction about how to do this kind of research. Three versions of the assignment are provided. In all three, students read a news story and the original report on which the article was based, and they complete a worksheet with guidelines for summarizing the reported study. In some versions students are supplied the news story and report and in another each student finds a news article and tracks down the original report on her own. Included here are our guidelines, example instructional packets, and the process we use to organize each type of assignment.

scholarly journals Risk Scoring System of Mortality and Prediction Model of Hospital Stay for Critically Ill Patients Receiving Parenteral Nutrition

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 853
Author(s):  
Jee-Yun Kim ◽  
Jeong Yee ◽  
Tae-Im Park ◽  
So-Youn Shin ◽  
Man-Ho Ha ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Linear Regression ◽  
Parenteral Nutrition ◽  
Prediction Model ◽  
Scoring System ◽  
Prediction Equation ◽  
Icu Patients ◽  
Risk Scoring ◽  
Risk Scoring System

Predicting the clinical progression of intensive care unit (ICU) patients is crucial for survival and prognosis. Therefore, this retrospective study aimed to develop the risk scoring system of mortality and the prediction model of ICU length of stay (LOS) among patients admitted to the ICU. Data from ICU patients aged at least 18 years who received parenteral nutrition support for ≥50% of the daily calorie requirement from February 2014 to January 2018 were collected. In-hospital mortality and log-transformed LOS were analyzed by logistic regression and linear regression, respectively. For calculating risk scores, each coefficient was obtained based on regression model. Of 445 patients, 97 patients died in the ICU; the observed mortality rate was 21.8%. Using logistic regression analysis, APACHE II score (15–29: 1 point, 30 or higher: 2 points), qSOFA score ≥ 2 (2 points), serum albumin level < 3.4 g/dL (1 point), and infectious or respiratory disease (1 point) were incorporated into risk scoring system for mortality; patients with 0, 1, 2–4, and 5–6 points had approximately 10%, 20%, 40%, and 65% risk of death. For LOS, linear regression analysis showed the following prediction equation: log(LOS) = 0.01 × (APACHE II) + 0.04 × (total bilirubin) − 0.09 × (admission diagnosis of gastrointestinal disease or injury, poisoning, or other external cause) + 0.970. Our study provides the mortality risk score and LOS prediction equation. It could help clinicians to identify those at risk and optimize ICU management.

scholarly journals AB1329-HPR THE CURRENT STATUS AND ASSOCIATED FACTORS OF FATIGUE IN CHINESE PATIENTS WITH GOUT

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1953.3-1953
Author(s):  
J. Guo ◽  
W. Zhou ◽  
M. He ◽  
Z. Gu ◽  
C. Dong
Keyword(s):  
Multiple Sclerosis ◽  
Logistic Regression ◽  
Linear Regression ◽  
Sleep Quality ◽  
Binary Logistic Regression ◽  
Psychological Status ◽  
Functional Disorder ◽  
Stepwise Linear Regression ◽  
Chi Square Analysis ◽  
Anxiety Depression

Background:Fatigue of chronic diseases has been paid more and more attention. but the status of fatigue in gout patients has not been reported all the world[1].Objectives:In the absence of previous studies, our study aims to investigate the fatigue status, explore the potential predictors of fatigue and the effects of fatigue on health-related quality of life (HRQoL) among Chinese gout patients.Methods:This cross-sectional study was conducted from the Affiliated Hospital of Nantong University. A series of questionnaires were applied: Fatigue Scale-14 (FS-14), the 10 cm visual analog scale (VAS), the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder questionnaire (GAD-7), the Pittsburgh Sleep Quality Index (PSQI), Health Assessment Questionnaire(HAQ), the Short Form 36 health survey (SF-36). Laboratory examinations were taken to obtain some biochemical indicators. Independent samples t-test, Mann–Whitney U-test, Chi-square analysis, Pearson /Spearman correlation, Stepwise linear regression and binary logistic regression were used to analyze the data.Results:411 gout patients were included in this study. Among them, more than 50% patients reported physical fatigue in FS-14, severe disease, poor psychological status and reduced HRQoL were associated with fatigue. Multiple stepwise linear regression and binary logistic regression were applied and showed that pain, sleep quality, anxiety, depression and functional disorder were the potential predictors of fatigue. In addition, we found that the more severe the fatigue, the lower the patient’s HRQoL.Conclusion:Fatigue among gout patients is exceedingly common. The results of this study suggested that rheumatologists should pay closely attention to gout patients who suffer from serious fatigue, especially those with pain, poorer sleep quality, anxiety, depression and functional disorder.References:[1]Henry, A., Tourbah, A., Camus, G., Deschamps, R., Mailhan, L., Castex, C., Gout, O. & Montreuil, M. (2019) Anxiety and depression in patients with multiple sclerosis: The mediating effects of perceived social support, Multiple sclerosis and related disorders. 27, 46-51.Disclosure of Interests:None declared

scholarly journals Regression analyses of questionnaires in bedside teaching

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Wolf Ramackers ◽  
Julia Victoria Stupak ◽  
Indra Louisa Marcheel ◽  
Annette Tuffs ◽  
Harald Schrem ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Linear Regression ◽  
Survey Data ◽  
Organizational Structures ◽  
Bedside Teaching ◽  
Regression Analyses ◽  
Negative Perception ◽  
Data Analyses ◽  
Main Target ◽  
Relevant Factors

Abstract Background Students’ ratings of bedside teaching courses are difficult to evaluate and to comprehend. Validated systematic analyses of influences on students’ perception and valuation of bedside teaching can serve as the basis for targeted improvements. Methods Six hundred seventy-two observations were conducted in different surgical departments. Survey items covered the categories teacher’s performance, student’s self-perception and organizational structures. Relevant factors for the student overall rating were identified by multivariable linear regression after exclusion of variable correlations > 0.500. The main target for intervention was identified by the 15% worst overall ratings via multivariable logistic regression. Results According to the students the success of bedside teaching depended on their active participation and the teacher’s explanations of pathophysiology. Further items are both relevant to the overall rating and a possible negative perception of the session. In comparison, negative perception of courses (worst 15%) is influenced by fewer variables than overall rating. Variables that appear in both calculations show slight differences in their weighing for their respective endpoints. Conclusion Relevant factors for overall rating and negative perception in bedside teaching can be identified by regression analyses of survey data. Analyses provide the basis for targeted improvement.

Cross-Sectional Examination of Homocysteine Levels with Sarcopenia and Its Components in Memory Clinic Outpatients

2021 ◽  
pp. 1-10
Author(s):  
Yosuke Yamada ◽  
Hiroyuki Umegaki ◽  
Fumie Kinoshita ◽  
Chi Hsien Huang ◽  
Taiki Sugimoto ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Cognitive Impairment ◽  
Cognitive Function ◽  
Linear Regression ◽  
Logistic Regression Analysis ◽  
Linear Regression Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Memory Clinic ◽  
Cross Sectional

Background: Homocysteine is a common risk factor for cognitive impairment and sarcopenia. However, very few studies have shown an association between sarcopenia and serum homocysteine levels after adjustment for cognitive function. Objective: The purpose of this study was to investigate the relationship between homocysteine and sarcopenia in memory clinic patients. Methods: This cross-sectional study investigated outpatients in a memory clinic. We enrolled 1,774 participants (≥65 years old) with measured skeletal muscle mass index (SMI), hand grip strength (HGS), and homocysteine. All participants had undergone cognitive assessments and were diagnosed with dementia, mild cognitive impairment, or normal cognition. Patient characteristics were compared according to sarcopenia presence, SMI level, or HGS. Multivariate logistic regression analysis was performed to determine the association of homocysteine with sarcopenia, low SMI, or low HGS. Next, linear regression analysis was performed using HGS as a continuous variable. Results: Logistic regression analysis showed that low HGS was significantly associated with homocysteine levels (p = 0.002), but sarcopenia and low SMI were not. In linear regression analysis, HGS was negatively associated with homocysteine levels after adjustment for Mini-Mental State Examination score (β= –2.790, p <  0.001) or clinical diagnosis of dementia (β= –3.145, p <  0.001). These results were similar for men and women. Conclusion: Our results showed a negative association between homocysteine and HGS after adjustment for cognitive function. Our findings strengthen the assumed association between homocysteine and HGS. Further research is needed to determine whether lower homocysteine levels lead to prevent muscle weakness.

Epic Cruelty: On Post-Pandemic Performance

2021 ◽  
Vol 37 (2) ◽  
pp. 119-136
Author(s):  
Rick Mitchell
Keyword(s):  
Climate Change ◽  
United States ◽  
African Americans ◽  
The United States ◽  
California State University ◽  
The State ◽  
State University ◽  
White Supremacist ◽  
Systemic Racism ◽  
Disaster Capitalism

As today’s catastrophic Covid-19 pandemic exacerbates ongoing crises, including systemic racism, rising ethno-nationalism, and fossil-fuelled climate change, the neoliberal world that we inhabit is becoming increasingly hostile, particularly for the most vulnerable. Even in the United States, as armed white-supremacist, pro-Trump forces face off against protesters seeking justice for African Americans, the hostility is increasingly palpable, and often frightening. Yet as millions of Black Lives Matter protesters demonstrated after the brutal police killing of George Floyd, the current, intersecting crises – worsened by Trump’s criminalization of anti-racism protesters and his dismissal of science – demand a serious, engaged, response from activists as well as artists. The title of this article is meant to evoke not only the state of the unusually cruel moment through which we are living, but also the very different approaches to performance of both Brecht and Artaud, whose ideas, along with those of others – including Benjamin, Butler, Latour, Mbembe, and Césaire – inform the radical, open-ended, post-pandemic theatre practice proposed in this essay. A critically acclaimed dramatist as well as Professor of English and Playwriting at California State University, Northridge, Mitchell’s published volumes of plays include Disaster Capitalism; or Money Can’t Buy You Love: Three Plays; Brecht in L.A.; and Ventriloquist: Two Plays and Ventriloquial Miscellany. He is the editor of Experimental O’Neill, and is currently at work on a series of post-pandemic plays.

scholarly journals Right choice of a method for determination of cut-off values: A statistical tool for a diagnostic test

2014 ◽  
Vol 5 (3) ◽  
pp. 30-34 ◽  
Author(s):  
Balkishan Sharma ◽  
Ravikant Jain
Keyword(s):  
Logistic Regression ◽  
Discriminant Analysis ◽  
Diagnostic Test ◽  
Roc Curve ◽  
Traditional Method ◽  
Statistical Technique ◽  
Curve Analysis ◽  
Operating Characteristics ◽  
Roc Curve Analysis

Objective: The clinical diagnostic tests are generally used to identify the presence of a disease. The cutoff value of a diagnostic test should be chosen to maximize the advantage that accrues from testing a population of human and others. When a diagnostic test is to be used in a clinical condition, there may be an opportunity to improve the test by changing the cutoff value. To enhance the accuracy of diagnosis is to develop new tests by using a proper statistical technique with optimum sensitivity and specificity. Method: Mean±2SD method, Logistic Regression Analysis, Receivers Operating Characteristics (ROC) curve analysis and Discriminant Analysis (DA) have been discussed with their respective applications. Results: The study highlighted some important methods to determine the cutoff points for a diagnostic test. The traditional method is to identify the cut-off values is Mean±2SD method. Logistic Regression Analysis, Receivers Operating Characteristics (ROC) curve analysis and Discriminant Analysis (DA) have been proved to be beneficial statistical tools for determination of cut-off points.Conclusion: There may be an opportunity to improve the test by changing the cut-off value with the help of a correctly identified statistical technique in a clinical condition when a diagnostic test is to be used. The traditional method is to identify the cut-off values is Mean ± 2SD method. It was evidenced in certain conditions that logistic regression is found to be a good predictor and the validity of the same can be confirmed by identifying the area under the ROC curve. Abbreviations: ROC-Receiver operating characteristics and DA-Discriminant Analysis. Asian Journal of Medical Science, Volume-5(3) 2014: 30-34 http://dx.doi.org/10.3126/ajms.v5i3.9296      

scholarly journals California State University

1986 ◽  
Vol 70 (493) ◽  
pp. 71-73
Author(s):  
Walter F. Beckman
Keyword(s):  
California State University ◽  
State University
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