scholarly journals How Persistent Is the Occupation-Education Mismatch in Canada?

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Keyword(s):  
Survival Analysis ◽  
Cox Model ◽  
Education Level ◽  
Time Varying ◽  
Proportional Hazard ◽  
Regression Analyses ◽  
Job Match ◽  
Probability Of Transition ◽  
The Impact ◽  
Over Time

This paper investigates the duration of overqualification in Canada, the time-varying probability of leaving overqualification, and the wage consequences associated with the transition. The paper also applies a survival analysis approach to examine the impact of key driving factors on the probability of transitioning from overqualification to a job match using a proportional hazard (Cox) model. The analysis shows that within a 5-year period, an overqualified worker has a 22 percent probability of transitioning to an occupation that matches the education level. The probability of transition also decreases quickly over time, thus lowering the chances of finding a job match after 12 months. Regression analyses also provide evidence that overqualified workers with short tenure are more likely to transition than workers with medium to long tenure. Finally, job-related training nearly doubles the chance of transitioning out of overqualification.

scholarly journals Effects of Time-Varying Parent Input on Children’s Language Outcomes Differ for Vocabulary and Syntax

2021 ◽  
pp. 095679762097055
Author(s):  
Catriona Silvey ◽  
Özlem Ece Demir-Lira ◽  
Susan Goldin-Meadow ◽  
Stephen W. Raudenbush
Keyword(s):  
Standardized Tests ◽  
Child Outcomes ◽  
Time Varying ◽  
Syntactic Complexity ◽  
Language Outcomes ◽  
Optimal Sequence ◽  
Linguistic Input ◽  
Language Input ◽  
The Impact ◽  
Over Time

Early linguistic input is a powerful predictor of children’s language outcomes. We investigated two novel questions about this relationship: Does the impact of language input vary over time, and does the impact of time-varying language input on child outcomes differ for vocabulary and for syntax? Using methods from epidemiology to account for baseline and time-varying confounding, we predicted 64 children’s outcomes on standardized tests of vocabulary and syntax in kindergarten from their parents’ vocabulary and syntax input when the children were 14 and 30 months old. For vocabulary, children whose parents provided diverse input earlier as well as later in development were predicted to have the highest outcomes. For syntax, children whose parents’ input substantially increased in syntactic complexity over time were predicted to have the highest outcomes. The optimal sequence of parents’ linguistic input for supporting children’s language acquisition thus varies for vocabulary and for syntax.

scholarly journals Differences in risk perception, knowledge and protective behaviour regarding COVID-19 by education level among women and men in Germany. Results from the COVID-19 Snapshot Monitoring (COSMO) study

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251694
Author(s):  
Petra Rattay ◽  
Niels Michalski ◽  
Olga Maria Domanska ◽  
Anna Kaltwasser ◽  
Freia De Bock ◽  
...  
Keyword(s):  
Risk Perception ◽  
Education Level ◽  
Factual Knowledge ◽  
Perceived Severity ◽  
Highly Educated ◽  
Interaction Terms ◽  
Protective Behaviour ◽  
Low Education ◽  
The Impact ◽  
Over Time

The main strategy for combatting SARS-CoV-2 infections in 2020 consisted of behavioural regulations including contact reduction, maintaining distance, hand hygiene, and mask wearing. COVID-19-related risk perception and knowledge may influence protective behaviour, and education could be an important determinant. The current study investigated differences by education level in risk perception, knowledge and protective behaviour regarding COVID-19 in Germany, exploring the development of the pandemic over time. The COVID-19 Snapshot Monitoring study is a repeated cross-sectional online survey conducted during the pandemic in Germany from 3 March 2020 (waves 1–28: 27,957 participants aged 18–74). Differences in risk perception, knowledge and protective behaviour according to education level (high versus low) were analysed using linear and logistic regression. Time trends were accounted for by interaction terms for education level and calendar week. Regarding protective behaviour, interaction terms were tested for all risk perception and knowledge variables with education level. The strongest associations with education level were evident for perceived and factual knowledge regarding COVID-19. Moreover, associations were found between low education level and higher perceived severity, and between low education level and lower perceived probability. Highly educated men were more worried about COVID-19 than those with low levels of education. No educational differences were observed for perceived susceptibility or fear. Higher compliance with hand washing was found in highly educated women, and higher compliance with maintaining distance was found in highly educated men. Regarding maintaining distance, the impact of perceived severity differed between education groups. In men, significant moderation effects of education level on the association between factual knowledge and all three protective behaviours were found. During the pandemic, risk perception and protective behaviour varied greatly over time. Overall, differences by education level were relatively small. For risk communication, reaching all population groups irrespective of education level is critical.

scholarly journals Joint modelling of longitudinal and time-to-event data: An illustration using CD4 count and mortality in a cohort of patients initiated on antiretroviral therapy

2020 ◽  
Author(s):  
Nobuhle Nokubonga Mchunu ◽  
Henry Mwambi ◽  
Tarylee Reddy ◽  
Nonhlanhla Yende-Zuma ◽  
Kogieleum Naidoo
Keyword(s):  
Cox Model ◽  
Joint Model ◽  
Cd4 Count ◽  
Time Varying ◽  
Event Data ◽  
Time To Event ◽  
Joint Modelling ◽  
Risk Of Death ◽  
Time To Event Data ◽  
Over Time

Abstract Background: Modelling of longitudinal biomarkers and time-to-event data are important to monitor disease progression. However, these two variables are traditionally analyzed separately or time-varying Cox models are used. The former strategy fails to recognize the shared random-effects from the two processes while the latter assumes that longitudinal biomarkers are exogenous covariates, resulting in inefficient or biased estimates for the time-to-event model. Therefore, we used joint modelling for longitudinal and time-to-event data to assess the effect of longitudinal CD4 count on mortality. Methods: We studied 4014 patients from the Centre for the AIDS Programme of Research in South Africa (CAPRISA) who initiated ART between June 2004 and August 2013. We used proportional hazards regression model to assess the effect of baseline characteristics (excluding CD4 count) on mortality, and linear mixed effect models to evaluate the effect of baseline characteristics on the CD4 count evolution over time. Thereafter, the two analytical approaches were amalgamated to form an advanced joint model for studying the effect of longitudinal CD4 count on mortality. To illustrate the virtues of the joint model, the results from the joint model were compared to those from the time-varying Cox model. Results: Using joint modelling, we found that lower CD4 count over time was associated with a 1.3-fold increase in the risk of death, (HR: 1.34, 95% CI: 1.27-1.42). Whereas, results from the time-varying Cox model showed lower CD4 count over time was associated with a 1.2-fold increase in the risk of death, (HR: 1.17, 95% CI: 1.12-1.23). Conclusions: Joint modelling enabled the assessment of the effect of longitudinal CD4 count on mortality while correcting for shared random effects between longitudinal and time-to-event models. In the era of universal test and treat, the evaluation of CD4 count is still crucial for guiding the initiation and discontinuation of opportunistic infections prophylaxis and assessment of late presenting patients. CD4 count can also be used when immunological failure is suspected as we have shown that it is associated with mortality. Keywords: Time-to-event data; longitudinal data; joint models; CD4 count; mortality; bias

scholarly journals The social patterning of mortality in a cohort of elderly Swedes

1996 ◽  
pp. 101-110 ◽  
Author(s):  
Olle Lundberg ◽  
Ingemar Kåreholt
Keyword(s):  
Social Class ◽  
The Elderly ◽  
Retirement Age ◽  
Functional Abilities ◽  
Proportional Hazard ◽  
Class Differences ◽  
Death Registry ◽  
The Social ◽  
The Impact ◽  
Over Time

Social class differences in mortality among the elderly have received only limited interest. In this paper we analyze the impact of social class on mortality from mid-life onwards. In 1968 1,860 persons born between 1892 and 1915 were interviewed and followed in the national cause of death registry for the period 1968-1991. In addition. 537 of the 563 survivors were fe-interviewed in 1992. We employ proportional hazard regressions to analyze the impact of social class on death risks over time. There are fairly small class differences in the probability of reaching old age. However, it appears that mortality differentials were steeper before retirement age than after. Still, the size of class differences in mortality seem smaller than expected on the basis of other studies. At the same time steep class gradients in illness and functional abilities exist among survivors. Some possible explanations for these somewhat contradictory findings are discussed.

scholarly journals Advances in diagnostic practices affect thyroid cancer incidence in France

2004 ◽  
pp. 133-139 ◽  
Author(s):  
L Leenhardt ◽  
MO Bernier ◽  
MH Boin-Pineau ◽  
B Conte Devolx ◽  
R Marechaud ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Cancer Incidence ◽  
Thyroid Diseases ◽  
Proportional Hazard ◽  
Clinical Practices ◽  
Cancer Prevalence ◽  
Diagnostic Practices ◽  
The Impact ◽  
Thyroid Cancer Incidence ◽  
Over Time

OBJECTIVE: To analyse trends in diagnostic practices of thyroid diseases and to relate them to the increase in thyroid cancer incidence in France over time. DESIGN: From 1980 to 2000, a French retrospective multicentric (three endocrinology and three nuclear medicine centres) study of thyroid diseases was conducted on 20 consecutive unselected patients' records, sampled every 5 years in each centre. METHODS: Characteristics of the population and diagnosis procedures (thyroid ultrasonography (US), radionuclide scan, cytology and hormonal measurements) were described over time. Changing trends in operated patients and in cancer prevalence were analysed as well as the impact of practices on cancer incidence. RESULTS: The study included 471 patients (82% female, mean age 46.7, range 9-84 years), referred for nodular thyroid diseases (66.7%) or thyroid dysfunctions (33.3%). A significant increase in US (3 to 84.8%) and cytological practices (4.5 to 23%), and a decrease (89.4 to 49.6%) in radionuclide scan procedures were observed over time. Although the proportion of patients undergoing surgery remained constant (24.8%), the prevalence of cancer increased among operated patients from 12.5 to 37% (P=0.006). In a Cox's proportional hazard model stratified on the clinical characteristics of patients, only the cytological practice, regardless of its results, was significantly associated with the occurrence of cancer: relative risk (RR)=4.4 (95% confidence interval (CI): 1.1-16; P=0.04). CONCLUSIONS: From 1980 to 2000, a major evolution in clinical practices has led to the increase in thyroid cancer reported in France. Such changes in medical, as well as in surgical and pathological, practices must be taken into account in incidence measurement.

scholarly journals Impact of Model Choice When Studying the Relationship Between Blood Pressure Variability and Risk of Stroke Recurrence

Hypertension ◽  
2021 ◽  
Author(s):  
Hugues de Courson ◽  
Loïc Ferrer ◽  
Antoine Barbieri ◽  
Phillip J. Tully ◽  
Mark Woodward ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Blood Pressure Variability ◽  
Proportional Hazards ◽  
Cox Model ◽  
Positive Association ◽  
Vascular Risk Factor ◽  
Stroke Recurrence ◽  
The Impact ◽  
Over Time

Long-term blood pressure variability (BPV), an increasingly recognized vascular risk factor, is challenging to analyze. The objective was to assess the impact of BPV modeling on its estimated effect on the risk of stroke. We used data from a secondary stroke prevention trial, PROGRESS (Perindopril Protection Against Stroke Study), which included 6105 subjects. The median number of blood pressure (BP) measurements was 12 per patient and 727 patients experienced a first stroke recurrence over a mean follow-up of 4.3 years. Hazard ratios (HRs) of BPV were estimated from 6 proportional hazards models using different BPV modeling for comparison purposes. The 3 commonly used methods first derived SD of BP measures observed over a given period of follow-up and then used it as a fixed covariate in a Cox model. The 3 more advanced modeling accounted for changes in BP or BPV over time in a single-stage analysis. While the 3 commonly used methods produced contradictory results (for a 5 mmHg increase in BPV, HR=0.75 [95% CI, 0.68–0.82], HR=0.99 [0.91–1.08], HR=1.19 [1.10–1.30]), the 3 more advanced modeling resulted in a similar moderate positive association (HR=1.08 [95% CI, 0.99–1.17]), whether adjusted for BP at randomization or mean BP over the follow-up. The method used to assess BPV strongly affects its estimated effect on the risk of stroke, and should be chosen with caution. Further methodological developments are needed to account for the dynamics of both BP and BPV over time, to clarify the specific role of BPV.

scholarly journals Measuring the Dynamic Risk of Further Offending: A Feasibility Study

2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Helen Hodges ◽  
Kevin Fahey
Keyword(s):  
Social Services ◽  
Feasibility Study ◽  
Justice System ◽  
Assessment Tool ◽  
Criminal History ◽  
Time Varying ◽  
Policy And Practice ◽  
The Core ◽  
The Impact ◽  
Over Time

BackgroundYoung people who have offended were, until recently, assessed using the Core ASSET Profile – a tool which determined their likelihood of reoffending based on their criminal history and practitioner scores across 12 domains. The repeated assessments provide a set of data for each individual which can be used to model how their risk of further offending varies over time. Having conducted an initial proof of concept study, this work explores the potential of extending the range of ‘risk’ and ‘protective’ factors using anonymised linked data held within the SAIL Databank. Main AimThe feasibility study is designed to establish the potential for using administrative data to develop a more sensitive assessment tool for use in the youth justice system. Specifically, the study explores the impact of being care experienced and of subsequent system contact in elevating the risk of further offending. ApproachA series of Bayesian hierarchical models will be generated which mimic the features of the Core ASSET Profile under the Scaled Approach. These include a range of time-varying and non-time varying variables matched to the individual, drawn from education, health and social services datasets as well as their court and offending records. ResultsThe anticipated findings will advance our understanding of how the likelihood of further offending varies over time for different groups, and how further system contact increases the risk. This will enable the complexity of young people’s real lives to be explored, and hence appropriate and timely interventions to be developed. ConclusionModelling under a Bayesian framework affords the opportunity to generate robust analysis based on smaller datasets. Findings have significant implications for policy and practice, particularly in the context of assessment processes across the justice system and social welfare.

scholarly journals Heart Failure After Myocardial Infarction - A Population-Based Study

Circulation ◽  
2001 ◽  
Vol 103 (suppl_1) ◽  
pp. 1359-1359
Author(s):  
Jens P Hellermann ◽  
Steven J Jacobsen ◽  
Barbara P Yawn ◽  
Susan Weston ◽  
Margaret M Redfield ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Heart Failure ◽  
Clinical Characteristics ◽  
Reperfusion Therapy ◽  
Population Based ◽  
Proportional Hazard ◽  
Population Based Study ◽  
History Of ◽  
The Impact ◽  
Over Time

P46 While heart failure (HF), an emerging epidemic, complicates myocardial infarction (MI), little is known on the predictors of HF post-MI, in particular the impact of reperfusion therapy. This population-based study was undertaken to examine the association between clinical characteristics and post-MI HF between 1979 and 1994. Hospitalized incident MIs were validated using enzymes, chest pain, and Minnesota coding of the ECG. Framingham criteria were used to ascertain both in- and outpatient HF. Proportional hazard regression was used to identify predictors of CHF. In the study period, 1657 patients (pts.) (mean age 67.2 ± 13.9 years, 43% women) had an incident MI. History of diabetes, hypertension and prior HF was found in 19%, 54% and 11% of pts respectively. After 5 years, 43% of pts had experienced HF. Factors independently associated with HF were (see table). There was a 2% decline per year in occurrence of HF. Adding reperfusion therapy in the model attenuated the association between year and HF (adjusted RR for reperfusion 0.67, 95% CI 0.53, 0.84, p=0.006; adjusted for year 0.99; 95% CI 0.97, 1.01, p=0.37). Thus, while remaining frequent post-MI CHF has declined over time. Reperfusion therapy accounted for most of the effect of year. Table 1.

scholarly journals FRANCHISOR-FRANCHISEE RELATIONSHIP QUALITY: TIME OF RELATIONSHIP AND PERFORMANCE

2016 ◽  
Vol 56 (6) ◽  
pp. 600-610 ◽  
Author(s):  
LUÍS FERNANDO VAROTTO ◽  
JURACY GOMES PARENTE
Keyword(s):  
Financial Performance ◽  
Relationship Quality ◽  
Moderating Effect ◽  
Self Report ◽  
Regression Analyses ◽  
Relationship Duration ◽  
And Performance ◽  
The Impact ◽  
The Relationship ◽  
Over Time

ABSTRACT Franchise literature disputes how the relationship between franchisors and franchisees develops over time. Traditional lifecycle theory views relationships following an ascendant curve, in which relationship quality and performance strengthen over time. Another perspective better reflects the peculiarities of the franchisor-franchisee relationship, indicating that relationship quality in franchise systems follows a U-shaped curve. There is also limited research on the moderating effect of time on the relationship between relational variables and outcomes. This study sheds light on the influence of relationship duration on relationship quality and financial performance in the franchisee-franchisor relationship. Using a self-report survey from a sample of 342 franchisees, mean and regression analyses are conducted to test relationships. Results confirm the time effect on franchisor-franchisee relationship quality and performance, but the hypothesized shape of relationship phases is only partially confirmed. Moreover, time has a positive moderating effect on the impact of relationship quality on financial performance.

scholarly journals Joint modelling of longitudinal and time-to-event data: an illustration using CD4 count and mortality in a cohort of patients initiated on antiretroviral therapy

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Nobuhle N. Mchunu ◽  
Henry G. Mwambi ◽  
Tarylee Reddy ◽  
Nonhlanhla Yende-Zuma ◽  
Kogieleum Naidoo
Keyword(s):  
Cox Model ◽  
Joint Model ◽  
Cd4 Count ◽  
Time Varying ◽  
Event Data ◽  
Time To Event ◽  
Joint Modelling ◽  
Risk Of Death ◽  
Time To Event Data ◽  
Over Time

Abstract Background Modelling of longitudinal biomarkers and time-to-event data are important to monitor disease progression. However, these two variables are traditionally analyzed separately or time-varying Cox models are used. The former strategy fails to recognize the shared random-effects from the two processes while the latter assumes that longitudinal biomarkers are exogenous covariates, resulting in inefficient or biased estimates for the time-to-event model. Therefore, we used joint modelling for longitudinal and time-to-event data to assess the effect of longitudinal CD4 count on mortality. Methods We studied 4014 patients from the Centre for the AIDS Programme of Research in South Africa (CAPRISA) who initiated ART between June 2004 and August 2013. We used proportional hazards regression model to assess the effect of baseline characteristics (excluding CD4 count) on mortality, and linear mixed effect models to evaluate the effect of baseline characteristics on the CD4 count evolution over time. Thereafter, the two analytical approaches were amalgamated to form an advanced joint model for studying the effect of longitudinal CD4 count on mortality. To illustrate the virtues of the joint model, the results from the joint model were compared to those from the time-varying Cox model. Results Using joint modelling, we found that lower CD4 count over time was associated with a 1.3-fold increase in the risk of death, (HR: 1.34, 95% CI: 1.27-1.42). Whereas, results from the time-varying Cox model showed lower CD4 count over time was associated with a 1.2-fold increase in the risk of death, (HR: 1.17, 95% CI: 1.12-1.23). Conclusions Joint modelling enabled the assessment of the effect of longitudinal CD4 count on mortality while correcting for shared random effects between longitudinal and time-to-event models. In the era of universal test and treat, the evaluation of CD4 count is still crucial for guiding the initiation and discontinuation of opportunistic infections prophylaxis and assessment of late presenting patients. CD4 count can also be used when immunological failure is suspected as we have shown that it is associated with mortality.

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