scholarly journals Statistical models for longitudinal zero-inflated count data: application to seizure attacks

2019 ◽  
Vol 19 (3) ◽  
pp. 2555-2564
Author(s):  
Fenta Haile Mekonnen ◽  
Workie Demeke Lakew ◽  
Zike Dereje Tesfaye ◽  
Prafulla Kumar Swain
Keyword(s):  
Risk Factors ◽  
Epileptic Seizure ◽  
Count Data ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Negative Binomial ◽  
P Value ◽  
Longitudinal Outcome ◽  
Seizure Attacks

Background: Chronic non-communicable diseases:- such as epilepsy, are increasingly recognized as public health problems in developing and African countries. This study aimed at finding determinants of the number of epileptic seizure attacks using different count data modeling techniques.Methods: Four common fixed-effects Poisson family models were reviewed to analyze the count data with a high proportion of zeros in longitudinal outcome, i.e., the number of seizure attacks in epilepsy patients. This is because, in addition to the problem of extra zeros, the correlation between measurements upon the same patient at different occasions needs to be taken into consideration.Results: The investigation remarkably identified some important factors associated with epileptic seizure attacks. As people grow old , the number of seizure attacks increased and male patients had more seizures than their female counterparts. In general, a patient’s age, sex, monthly income, family history of epilepsy andservice satisfaction were some of the significant factors responsible for the frequency of seizure attacks (P value<0.05).Conclusion: This study suggests that zero-inflated negative binomial is the best model for predicting and describing the number of seizure attacks as well as identifying the potential risk factors. Addressing these risk factors will definitely contain the progression of seizure attack.Keywords: linear mixed model, hurdle model, seizure attacks, zero-inflated models.

scholarly journals 163 Annual differences in fecal egg counts in a forage-based ram test

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 172-172
Author(s):  
Morgan Van Davelaar ◽  
David R Notter ◽  
D Lee Wright ◽  
Anna M Zajac ◽  
Scott P Greiner ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Negative Binomial ◽  
Random Effect ◽  
Summer Precipitation ◽  
Parasite Load ◽  
Least Square ◽  
Birth Type ◽  
Normally Distributed

Abstract The objective was to determine the magnitude of yearly differences in parasite load in growing ram lambs. Data were obtained from the Southwest Virginia Agriculture Research and Extension Center in Glade Spring, VA. The center conducts a forage-based ram growth test during the summer where rams also undergo a parasite challenge. Data consisted of 488 Katahdin rams tested from 2012 to 2018. Rams were dewormed at delivery, and at the start of the test, each ram received an oral dose of 5,000 H. contortus larvae adjusted for body weight. Fecal egg count was measured 70 d later when rams were on average (SD) 200 (18) d old. Fecal egg counts were not normally distributed. The Box-Cox procedure indicated that a log transformation was appropriate, but the residuals were not normally distributed for several linear models. A zero-inflated negative binomial generalized linear mixed model was used for data analysis with the glmmTMB package in R. The model included fixed effects of centered and scaled weight, centered and scaled age, year, birth type, and rearing type, and the random effect of consignor. Birth type, rear type, and age were not significant (P &gt; 0.10). The least square mean (SE) fecal egg counts by year were 344 (118) for 2012, 623 (214) for 2013, 574 (195) for 2014, 1,125 (409) for 2015, 745 (253) for 2016, 408 (142) for 2017, and 239 (86) for 2018. Differences in summer precipitation could affect average parasite load. Despite similar total summer precipitation, 2012 had 1 extremely wet month whereas, 2015 had consistent precipitation throughout the summer. We conclude that producers should not compare fecal egg counts across years because the overall average may be multiple-fold different from year to year. Ranking rams within year will be more effective to select for improved parasite resistance.

Analyzing discontinuities in longitudinal count data: A multilevel generalized linear mixed model.

2020 ◽  
Author(s):  
James L. Peugh ◽  
Sarah J. Beal ◽  
Meghan E. McGrady ◽  
Michael D. Toland ◽  
Constance Mara
Keyword(s):  
Count Data ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Generalized Linear Mixed Model ◽  
Longitudinal Count Data

Identifying patients with CKD risk at the time of nephrectomy: When to initiate nephrology consult

2021 ◽  
pp. 239936932110319
Author(s):  
Yihe Yang ◽  
Zachary Kozel ◽  
Purva Sharma ◽  
Oksana Yaskiv ◽  
Jose Torres ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multivariate Analysis ◽  
Radical Nephrectomy ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Interstitial Fibrosis ◽  
Kidney Neoplasm ◽  
Tubular Atrophy ◽  
Independent Risk Factors

Introduction: The prevalence of chronic kidney disease (CKD) is high among kidney neoplasm patients because of the overlapping risk factors. Our purpose is to identify kidney cancer survivors with higher CKD risk. Methods: We studied a retrospective cohort of 361 kidney tumor patients with partial or radical nephrectomy. Linear mixed model was performed. Results: Of patients with follow-up >3 months, 84% were identified retrospectively to fulfill criteria for CKD diagnosis, although CKD was documented in only 15%. Urinalysis was performed in 205 (57%) patients at the time of nephrectomy. Multivariate analysis showed interstitial fibrosis and tubular atrophy (IFTA) >25% ( p = 0.005), severe arteriolar sclerosis ( p = 0.013), female gender ( p = 0.024), older age ( p = 0.012), BMI ⩾ 25 kg/m2 ( p < 0.001), documented CKD ( p < 0.001), baseline eGFR ⩽ 60 ml/min/1.73 m2 ( p < 0.001), and radical nephrectomy ( p < 0.001) were independent risk factors of lower eGFR at baseline and during follow-up. Average eGFR decreased within 3 months post nephrectomy. However, patients with different risk levels showed different eGFR time trend pattern at longer follow-ups. Multivariate analysis of time × risk factor interaction showed BMI, radical nephrectomy and baseline eGFR had time-dependent impact. BMI ⩾ 25 kg/m2 and radical nephrectomy were associated with steeper eGFR decrease slope. In baseline eGFR > 90 ml/min/1.73 m2 group, eGFR rebounded to pre-nephrectomy levels during extended follow-up. In partial nephrectomy patients with baseline eGFR ⩾ 90 ml/min/1.73 m2 ( n = 61), proteinuria ( p < 0.001) and BMI ( p < 0.001) were independent risk factors of decreased eGFR during follow up. Conclusions: As have been suggested by others and confirmed by our study, proteinuria and CKD are greatly under-recognized. Although self-evident as a minimum workup for nephrectomy patients to include SCr, eGFR, urinalysis, and proteinuria, the need for uniform applications of this practice should be reinforced. Non-neoplastic histology evaluation is valuable and should include an estimate of global sclerosis% (GS) and IFTA%. Patients with any proteinuria and/or eGFR ⩽ 60 at the time of nephrectomy or in follow-up with urologists, and/or >25% GS or IFTA, should be referred for early nephrology consultation.

scholarly journals Joint modelling of correlated binary outcomes regarding the misconceptions of HIV transmission: a study with reference to the tertiary and vocational education trainees in Sri Lanka

2020 ◽  
Vol 7 (8) ◽  
pp. 2950
Author(s):  
Thilini Samarakoon ◽  
Niroshan Withanage ◽  
Nimalakith Samarakoon ◽  
Upul Lekamge ◽  
Nadesha De Silva
Keyword(s):  
Risk Factors ◽  
Vocational Education ◽  
Mixed Model ◽  
Hiv Transmission ◽  
Linear Mixed Model ◽  
Family Relationship ◽  
Binary Outcomes ◽  
Behavioral Risk Factors ◽  
Behavioral Risk ◽  
Level Of Education

Background: Currently, people infected with HIV are largely discriminated and discredited. Misunderstanding about the mechanism of HIV transmission has been identified as one reason for discrimination. This study assessed the socio-demographic and behavioral risk factors of the two misconceptions about HIV transmission, namely HIV is transmitted by sharing cups and plates with an HIV infected person (Myth 1) and HIV is transmitted by mosquito bites (Myth 2) among the trainees who were selected to the Tertiary and Vocational Education Training (TVET) Centers in Sri Lanka.Methods: This study applied stratified random sampling to select 955 respondents. A self-administered structured questionnaire was used to collect the data. Generalized linear mixed model (GLMM) approach was applied to find the associations between misconceptions about HIV and socio-demographic and behavioral risk factors of the trainees.Results: Level of education of trainees, family relationship, knowledge on sexual and reproductive health (SRH), knowledge about the risk of getting HIV after sexual intercourse, whether the trainee had participated in seminar or workshop on sexually transmitted diseases were identified as the possible factors to detect the knowledge about the misconceptions of HIV transmission.Conclusions: Even though the level of education among different social segments have not revealed remarkable differences in knowledge, the study convinced that the youth should be provided better awareness and education on STD and HIV through countrywide workshops and awareness programmes.

scholarly journals Exome-wide association studies in general and long-lived populations identify genetic variants related to human age

2020 ◽  
Author(s):  
Patrick Sin-Chan ◽  
Nehal Gosalia ◽  
Chuan Gao ◽  
Cristopher V. Van Hout ◽  
Bin Ye ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Large Scale ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Association Studies ◽  
Model Systems ◽  
P Value ◽  
Ashkenazi Jews ◽  
Association Analyses ◽  
Age Related

SUMMARYAging is characterized by degeneration in cellular and organismal functions leading to increased disease susceptibility and death. Although our understanding of aging biology in model systems has increased dramatically, large-scale sequencing studies to understand human aging are now just beginning. We applied exome sequencing and association analyses (ExWAS) to identify age-related variants on 58,470 participants of the DiscovEHR cohort. Linear Mixed Model regression analyses of age at last encounter revealed variants in genes known to be linked with clonal hematopoiesis of indeterminate potential, which are associated with myelodysplastic syndromes, as top signals in our analysis, suggestive of age-related somatic mutation accumulation in hematopoietic cells despite patients lacking clinical diagnoses. In addition to APOE, we identified rare DISP2 rs183775254 (p = 7.40×10−10) and ZYG11A rs74227999 (p = 2.50×10−08) variants that were negatively associated with age in either both sexes combined and females, respectively, which were replicated with directional consistency in two independent cohorts. Epigenetic mapping showed these variants are located within cell-type-specific enhancers, suggestive of important transcriptional regulatory functions. To discover variants associated with extreme age, we performed exome-sequencing on persons of Ashkenazi Jewish descent ascertained for extensive lifespans. Case-Control analyses in 525 Ashkenazi Jews cases (Males ≥ 92 years, Females ≥ 95years) were compared to 482 controls. Our results showed variants in APOE (rs429358, rs6857), and TMTC2 (rs7976168) passed Bonferroni-adjusted p-value, as well as several nominally-associated population-specific variants. Collectively, our Age-ExWAS, the largest performed to date, confirmed and identified previously unreported candidate variants associated with human age.

scholarly journals Goats Given Transdermal Flunixin Meglumine Displayed Less Pain Behavior After Castration

2020 ◽  
Author(s):  
Amanda Lee ◽  
Meggan Graves ◽  
Andrea Lear ◽  
Sherry Cox ◽  
Marc Caldwell ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Body Position ◽  
Random Effect ◽  
Pain Behavior ◽  
Bout Duration ◽  
Flunixin Meglumine ◽  
Meat Goats ◽  
Transdermal Application

AbstractPain management should be utilized with castration to reduce physiological and behavioral changes. Transdermal application of drugs require less animal management and fewer labor risks, which can occur with oral administration or injections. The objective was to determine the effects of transdermal flunixin meglumine on meat goats’ behavior post-castration. Male goats (N = 18; mean body weight ± standard deviation: 26.4 ± 1.6 kg) were housed individually in pens and randomly assigned to 1 of 3 treatments: (1) castrated, dosed with transdermal flunixin meglumine; (2) castrated, dosed with transdermal placebo; and (3) sham castrated, dosed with transdermal flunixin meglumine. Body position, rumination, and head- pressing were observed for 1 h ± 10 minutes twice daily on days −1, 0, 1, 2, and 5 around castration. Each goat was observed once every 5-minutes (scan samples) and reported as percentage of observations. Accelerometers were used to measure standing, lying, and laterality (total time, bouts, and bout duration). A linear mixed model was conducted using GLIMMIX. Fixed effects of treatment, day relative to castration, and treatment*day relative to castration and random effect of date and goat nested within treatment were included. Treatment 1 goats (32.7 ± 2.8%) and treatment 2 goats (32.5 ± 2.8%) ruminated less than treatment 3 goats (47.4 ± 2.8%, P = 0.0012). Head pressing was greater on day of castration in treatment 2 goats (P < 0.001). Standing bout duration was greatest in treatment 2 goats on day 1 post-castration (P < 0.001). Lying bout duration was greatest in treatment 2 goats on day 1 post-castration compared to treatment 1 and treatment 3 goats(P < 0.001). Transdermal flunixin meglumine improved goats’ fluidity of movement post-castration and decreased head pressing, indicating a mitigation of pain behavior.

Analysis of aggregation, a worked example: numbers of ticks on red grouse chicks

Parasitology ◽  
2001 ◽  
Vol 122 (5) ◽  
pp. 563-569 ◽  
Author(s):  
D. A. ELSTON ◽  
R. MOSS ◽  
T. BOULINIER ◽  
C. ARROWSMITH ◽  
X. LAMBIN
Keyword(s):  
Random Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Negative Binomial ◽  
Generalized Linear Mixed Model ◽  
Red Grouse ◽  
Worked Example ◽  
Fixed And Random Effects ◽  
Individual Effects ◽  
Lagopus Lagopus Scoticus

The statistical aggregation of parasites among hosts is often described empirically by the negative binomial (Poisson-gamma) distribution. Alternatively, the Poisson-lognormal model can be used. This has the advantage that it can be fitted as a generalized linear mixed model, thereby quantifying the sources of aggregation in terms of both fixed and random effects. We give a worked example, assigning aggregation in the distribution of sheep ticksIxodes ricinuson red grouseLagopus lagopus scoticuschicks to temporal (year), spatial (altitude and location), brood and individual effects. Apparent aggregation among random individuals in random broods fell 8-fold when spatial and temporal effects had been accounted for.

Generalized linear mixed models for multi-reader multi-case studies of diagnostic tests

2015 ◽  
Vol 26 (3) ◽  
pp. 1373-1388 ◽  
Author(s):  
Wei Liu ◽  
Norberto Pantoja-Galicia ◽  
Bo Zhang ◽  
Richard M Kotz ◽  
Gene Pennello ◽  
...  
Keyword(s):  
Mixed Models ◽  
Diagnostic Tests ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Generalized Linear Mixed Models ◽  
Characteristic Curve ◽  
Linear Mixed Models ◽  
Parametric Bootstrap ◽  
Pseudo Likelihood

Diagnostic tests are often compared in multi-reader multi-case (MRMC) studies in which a number of cases (subjects with or without the disease in question) are examined by several readers using all tests to be compared. One of the commonly used methods for analyzing MRMC data is the Obuchowski–Rockette (OR) method, which assumes that the true area under the receiver operating characteristic curve (AUC) for each combination of reader and test follows a linear mixed model with fixed effects for test and random effects for reader and the reader–test interaction. This article proposes generalized linear mixed models which generalize the OR model by incorporating a range-appropriate link function that constrains the true AUCs to the unit interval. The proposed models can be estimated by maximizing a pseudo-likelihood based on the approximate normality of AUC estimates. A Monte Carlo expectation-maximization algorithm can be used to maximize the pseudo-likelihood, and a non-parametric bootstrap procedure can be used for inference. The proposed method is evaluated in a simulation study and applied to an MRMC study of breast cancer detection.

scholarly journals Quantifying the Effects of Fusarium Head Blight on Grain Yield and Test Weight in Soft Red Winter Wheat

2015 ◽  
Vol 105 (3) ◽  
pp. 295-306 ◽  
Author(s):  
Jorge David Salgado ◽  
Laurence V. Madden ◽  
Pierce A. Paul
Keyword(s):  
Winter Wheat ◽  
Grain Yield ◽  
Fusarium Head Blight ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Test Weight ◽  
Head Blight ◽  
Soft Red Winter Wheat ◽  
Red Winter Wheat

Fusarium head blight (FHB), caused by the fungus Fusarium graminearum, is known to negatively affect wheat grain yield (YLD) and test weight (TW). However, very little emphasis has been placed on formally quantifying FHB–YLD and FHB–TW relationships. Field plots of three soft red winter wheat cultivars—‘Cooper’ (susceptible to FHB), ‘Hopewell’ (susceptible), and ‘Truman’ (moderately resistant)—were grown during the 2009, 2010, 2011, and 2012 seasons, and spray inoculated with spore suspensions of F. graminearum and Parastagonospora nodorum to generate a range of FHB and Stagonospora leaf blotch (SLB) levels. FHB index (IND) and SLB were quantified as percent diseased spike and flag leaf area, respectively, and YLD (kg ha−1) and TW (kg m−3) data were collected. Using IND as a continuous covariate and cultivar (CV) and SLB as categorical fixed effects, linear mixed-model regression analyses (LMMR) were used to model the IND–YLD and IND–TW relationship and to determine whether these relationships were influenced by CV and SLB. The final models fitted to the data were of the generic form y = a + b (IND), where a (intercept) or b (slope) could also depend on other factors. LMMR analyses were also used to estimate a and b by combining the studies from these 4 years with an additional 16 experiments conducted from 2003 to 2013, and bivariate random-effects meta-analysis was used to estimate population mean b ([Formula: see text]) and a (ā) for the IND–YLD relationship. YLD and TW decreased as IND increased, with b ranging from −3.2 to −2.3 kg m−3 %−1 for TW. For the IND–YLD relationship, [Formula: see text] was −51.7 kg ha−1 %IND−1 and ā was 4,426.7 kg ha−1. Neither cultivar nor SLB affected the IND–YLD relationship but SLB affected a of the IND–TW regression lines, whereas cultivar affected b. Plots with the highest levels of SLB (based on ordinal categories for SLB) had the lowest a and Hopewell had the highest b. The level of IND at which a 50-kg m−3 reduction in TW was predicted to occur was 19, 16, and 22% for Cooper, Hopewell, and Truman, respectively. A yield loss of 1 MT ha−1 was predicted to occur at 19% IND. The rate of reduction in relative TW or YLD per unit increase in IND was between −0.39 and −0.32%−1 for TW and −1.17%−1 for YLD. Results from this study could be integrated into more general models to evaluate the economics of FHB management strategies.

Misspecification of the random effect structure: Implications for the linear mixed model

2020 ◽  
Author(s):  
Brandon LeBeau
Keyword(s):  
Fixed Effects ◽  
Serial Correlation ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Type I Error ◽  
Random Effect ◽  
Correlated Data ◽  
Unbiased Estimation ◽  
Type I ◽  
Nested Data

<p>The linear mixed model is a commonly used model for longitudinal or nested data due to its ability to account for the dependency of nested data. Researchers typically rely on the random effects to adequately account for the dependency due to correlated data, however serial correlation can also be used. If the random effect structure is misspecified (perhaps due to convergence problems), can the addition of serial correlation overcome this misspecification and allow for unbiased estimation and accurate inferences? This study explored this question with a simulation. Simulation results show that the fixed effects are unbiased, however inflation of the empirical type I error rate occurs when a random effect is missing from the model. Implications for applied researchers are discussed.</p>

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