Statistical modeling of longitudinal survey data with binary outcomes

Data obtained from longitudinal surveys using complex multi-stage sampling designs contain cross-sectional dependencies among units caused by inherent hierarchies in the data, and within subject correlation arising due to repeated measurements. The statistical methods used for analyzing such data should account for stratification, clustering and unequal probability of selection as well as within-subject correlations due to repeated measurements. The complex multi-stage design approach has been used in the longitudinal National Population Health Survey (NPHS). This on-going survey collects information on health determinants and outcomes in a sample of the general Canadian population. This dissertation compares the model-based and design-based approaches used to determine the risk factors of asthma prevalence in the Canadian female population of the NPHS (marginal model). Weighted, unweighted and robust statistical methods were used to examine the risk factors of the incidence of asthma (event history analysis) and of recurrent asthma episodes (recurrent survival analysis). Missing data analysis was used to study the bias associated with incomplete data. To determine the risk factors of asthma prevalence, the Generalized Estimating Equations (GEE) approach was used for marginal modeling (model-based approach) followed by Taylor Linearization and bootstrap estimation of standard errors (design-based approach). The incidence of asthma (event history analysis) was estimated using weighted, unweighted and robust methods. Recurrent event history analysis was conducted using Anderson and Gill, Wei, Lin and Weissfeld (WLW) and Prentice, Williams and Peterson (PWP) approaches. To assess the presence of bias associated with missing data, the weighted GEE and pattern-mixture models were used.The prevalence of asthma in the Canadian female population was 6.9% (6.1-7.7) at the end of Cycle 5. When comparing model-based and design- based approaches for asthma prevalence, design-based method provided unbiased estimates of standard errors. The overall incidence of asthma in this population, excluding those with asthma at baseline, was 10.5/1000/year (9.2-12.1). For the event history analysis, the robust method provided the most stable estimates and standard errors. For recurrent event history, the WLW method provided stable standard error estimates. Finally, for the missing data approach, the pattern-mixture model produced the most stable standard errors To conclude, design-based approaches should be preferred over model-based approaches for analyzing complex survey data, as the former provides the most unbiased parameter estimates and standard errors

Evaluation of Spatio-temporal dynamics in agriculture in arid and semiarid region of Rajasthan, India-A statistical approach

The aridity of the arid and semiarid  region of Rajasthan, India is considered  as a great challenge for the growth of the crops due to lack of precipitation and high range of temperature. The present study focused on evaluating agricultural dynamics of the arid and semi-arid region of Rajasthan for the period of 2008-09 and 2021-22. The study comprised seven districts of Rajasthan: Barmer, Bikaner, Churu, Ganganagar, Hanumangarh, Jaisalmer and Jodhpur. Indices like crop combinations, crop diversity and agricultural efficiency of crops were taken into consideration. Hanumangarh showed 8 crop combinations to 4 from past to recent years viz. Bajra (Pennisetum glaucum), Guar seed (Cyamopsis tetragonoloba), Kharif pulses (Without Arhar) and Moth (Vigna aconitifolia), while in Jaisalmer, it was 3 crop combinations in the past while it is 6 in the recent years viz. Bajra, Guar seed , Moth , Mustard (Brassica), Mung (Vigna radiata) and Groundnut(Arachis hypogaea). A small percentage of Seasamum (Sesamum indicum) and  Cotton (LINT)(Gossypium) was in the past previous years, but now, it is almost negligible. Wheat (Triticum) was observed in a lower to moderate percentage share throughout the period. There was no change in the dominant crops except in Ganganagar and Churu district. All the districts had higher crop diversification in recent years except Barmer. The result of agricultural efficiency showed that Ganganagar, Jodhpur, Hanumangarh had higher agricultural efficiency (> 100), while Barmer had the least value (< 50). Agricultural Indices efficiently visualized temporal agriculture trends in arid and semiarid regions of Rajasthan

Review of West Bengal State adaptation policies, Indian Bengal Delta, WT6.1.2

This series is based on the work of the Deltas, Vulnerability and Climate Change: Migration and Adaptation (DECCMA) project, funded by Canada’s International Development Research Centre (IDRC) and the UK’s Department for International Development (DFID) through the Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA).The present report aims to identify, catalogue and evaluate the relevant existing State Government Policy/Plan documents on Climate Change Adaptation and related sectors (viz. Disaster Management, Agriculture, Water Resources, Forestry, Fisheries, Health, Energy, Rural Electrification, Poverty Alleviation, and Women Empowerment) in Indian Bengal Delta (IBD), in order to identify Government (State/Sundarbans Sector) Adaptation Responses to Climate Change variability, extremes and Climate Change induced threats to the population, in these islands

Review of Odisha State adaptation policies, Mahanadi Delta, WT6.1.2

This series is based on the work of the Deltas, Vulnerability and Climate Change: Migration and Adaptation (DECCMA) project, funded by Canada’s International Development Research Centre (IDRC) and the UK’s Department for International Development (DFID) through the Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA).Odisha, being one of the maritime states on the east coast of India, witnessed several historical devastating cyclones and other tropical storm surges, and with the process of climate change, it is considered one of the most vulnerable areas in the region. The Mahanadi Delta region in Odisha faces serious threats and challenges to safeguard land based resources and coastal resources supporting millions of coastal population in terms of climate change and related impacts viz. intense tropical cyclones, coastal erosion, land submergence, coastal inundation. The present situation demands attention and early actions for resilience to the impact of climate change through effective policy/plan changes

Review of national adaptation policies, India - WT6.1.2

This series is based on the work of the Deltas, Vulnerability and Climate Change: Migration and Adaptation (DECCMA) project, funded by Canada’s International Development Research Centre (IDRC) and the UK’s Department for International Development (DFID) through the Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA).This report is aimed at focusing on the issue of Adaptation with reference to Climate Change in Indian National Context. India being a signatory to UNFCCC and also to Kyoto Protocol, has been playing a active role in taking appropriate initiative to support “Adaptation”, as a part of action in the mainframe National Policies; besides, featuring Adaptation in the National Environment Policy in 2006 (23), India has also effectively incorporated the subject of Adaptation in the National Action Plan Climate Change in 2008(13) and in host of cross sectoral National Policies for e.g. Agriculture (16), Water (22), Forest (19), Energy (31), Livelihood Security (29;32), etc. This document presents a synoptic review based on Critical Analysis of National Policies and Action Plan which, have referred to the issue of Adaptation due to Climate Change, as an area of consideration

Maxillary sinus mucocele in a 20-year-old male: a case report of a rare occurrence

Mucocele of Maxillary sinus is a rare entity comprising 2-10% of all mucoceles and develops due to obstruction of drainage ostium. Here, we present a case of maxillary sinus mucocele in a 20-year-old male who presented with diffuse swelling on the left side of his face. Provisional diagnosis of mucocele was made on a computed tomography scan, which was later confirmed on histopathology. The lesion was managed surgically with uneventful healing at 2 weeks and 3 months follow-up. Mucoceles are often misdiagnosed as cysts or tumours of odontogenic origin on the conventional radiograph. Delay in diagnosis can result in complications due to the expansion of mucocele towards adjacent structures such as the nose and orbit. Therefore, it becomes crucial to diagnose it appropriately with the help of higher imaging modalities so that it can be managed well in time

Genomic biomarker discovery in disease progression and therapy response in bladder cancer utilizing machine learning

Cancer in all its forms of expression is a major cause of death. To identify the genomic reason behind cancer, discovery of biomarkers is needed. In this paper, genomic data of bladder cancer are examined for the purpose of biomarker discovery. Genomic biomarkers are indicators stemming from the study of the genome, either at a very low level based on the genome sequence itself, or more abstractly such as measuring the level of gene expression for different disease groups. The latter method is pivotal for this work, since the available datasets consist of RNA sequencing data, transformed to gene expression levels, as well as data on a multitude of clinical indicators. Based on this, various methods are utilized such as statistical modeling via logistic regression and regularization techniques (elastic-net), clustering, survival analysis through Kaplan–Meier curves, and heatmaps for the experiments leading to biomarker discovery. The experiments have led to the discovery of two gene signatures capable of predicting therapy response and disease progression with considerable accuracy for bladder cancer patients which correlates well with clinical indicators such as Therapy Response and T-Stage at surgery with Disease Progression in a time-to-event manner

High Serine-arginine Protein Kinase 1 Expression with PTEN Loss Defines Aggressive Phenotype of Prostate Cancer Associated with Lethal Outcome and Decreased Overall Survival

Background: Serine-arginine protein kinase 1 (SRPK1) has been implicated in prostate cancer (PCa) progression. However, its prognostic value and association with ERG and PTEN expression, two of the most common genetic alterations, have not been explored fully. Objective: We assessed the prognostic value of SRPK1 in association with ERG and PTEN in a cohort of patients managed nonsurgically by androgen deprivation therapy (ADT) for advanced disease. Design, setting, and participants: The study cohort consisted of men diagnosed with PCa by transurethral resection of the prostate (TURP; n = 480). The patients were divided into three main groups: incidental (patients with Gleason score [GS] ≤7 with no prior ADT), advanced (patients with GS ≥8 with no prior ADT), and castrate-resistant PCa (patients with prior ADT). Outcome measurements and statistical analysis: A total of 480 TURP samples were assessed by immunohistochemistry for SRPK1, ERG, and PTEN, and results were correlated with Gleason grade group (GG), overall survival (OS), and PCa-specific mortality (PCSM). Results and limitations: High SRPK1 expression was noted in 105/455 (23%) available patient cores. Expression of SRPK1 was associated with Gleason grade grouping (p \u3c 0.0001) with high expression detected in 22/74 (33%) with GG 5. High SRPK1 was not associated with ERG positivity (p = 0.18) but was significantly associated with PTEN intensity (p = 0.001). High SRPK1 was associated with OS (hazard ratio [HR] 1.99; confidence interval [CI]: 1.57–2.54, p \u3c 0.0001) and PCSM (HR 1.64; CI: 1.19–2.26, p \u3c 0.002). Adjusting for Gleason score, patients with high SRPK1 and negative PTEN had the worst clinical outcome for both OS and PCSM compared with other patients (p \u3c 0.0001, HR: 3.02; CI: 1.87–4.88 and HR: 6.40, CI: 3.19–12.85, respectively). Conclusions: High SRPK1 is associated with worse OS and PCSM. Moreover, patients with high SRPK1 expression and loss of PTEN had the worst clinical outcome for OS and cancer-specific mortality. Combined status of SRPK1 and PTEN may provide added value in stratifying patients into various prognostic groups. Patient summary: The expression of serine-arginine protein kinase 1 (SRPK1) combined with PTEN has a significant prognostic role in prostate cancer patients. Patients with high SRPK1 expression and negative PTEN had the worst clinical outcome for overall survival and cancer-specific mortality