Selecting a linear mixed model for longitudinal data: Repeated measures analysis of variance, covariance pattern model, and growth curve approaches.

2012 ◽  
Vol 17 (1) ◽  
pp. 15-30 ◽  
Author(s):  
Siwei Liu ◽  
Michael J. Rovine ◽  
Peter C. M. Molenaar
Keyword(s):  
Longitudinal Data ◽  
Analysis Of Variance ◽  
Growth Curve ◽  
Repeated Measures ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Repeated Measures Analysis

Linear mixed model better than repeated measures analysis

2019 ◽  
Vol 30 (6) ◽  
pp. NP1-NP2 ◽  
Author(s):  
Işıl Kutluturk Karagoz ◽  
Berhan Keskin ◽  
Flora Özkalaycı ◽  
Ali Karagöz
Keyword(s):  
Mixed Models ◽  
Repeated Measures ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Linear Time ◽  
Case Series ◽  
Model Fit ◽  
Repeated Measures Analysis ◽  
Technical Issues ◽  
Better Than

We have some criticism regarding some technical issues. Mixed models have begun to play a pivotal role in statistical analyses and offer many advantages over more conventional analyses regarding repeated variance analyses. First, they allow to avoid conducting multiple t-tests; second, they can accommodate for within-patient correlation; third, they allow to incorporate not only a random coefficient, but also a random slope, typically ‘linear’ time in longitudinal case series when there are enough data and patients’ trajectories vary a lot and improving model fit.

scholarly journals Changes in English Past Tense Use by Bilingual School-Age Children With and Without Developmental Language Disorder

2018 ◽  
Vol 61 (10) ◽  
pp. 2532-2546 ◽  
Author(s):  
Peggy F. Jacobson ◽  
Yan H. Yu
Keyword(s):  
Analysis Of Variance ◽  
Repeated Measures ◽  
Mixed Model ◽  
Language Disorder ◽  
School Age Children ◽  
Past Tense ◽  
The Novel ◽  
Developmental Language Disorder ◽  
Ability Group ◽  
Repeated Measures Analysis

PurposeThe purpose of this study is to examine changes in English past tense accuracy and errors among Spanish–English bilingual children with typical development (TD) and developmental language disorder (DLD).MethodThirty-three children were tested before and after 1 year to examine changes in clinically relevant English past tense errors using an elicited production task. A mixed-model linear regression using age as a continuous variable revealed a robust effect for age. A 4-way repeated-measures analysis of variance was conducted with age (young, old) and language ability group (TD, DLD) as between-subjects variables, time (Time 1, Time 2) and verb type (regular, irregular, and novel verbs) as within-subject variables, and percent accuracy as the dependent variable. Subsequently, a 4-way repeated-measures analysis of variance was conducted to measure the overall distribution of verb errors across 2 time points.ResultsOverall, children produced regular and novel verb past tense forms with higher accuracy than irregular past tense verbs in an elicitation task. Children with TD were more accurate than children with DLD. Younger children made more improvement than older children from Time 1 to Time 2, especially in the regular and novel verb conditions. Bare stem and overregularization were the most common errors across all groups. Errors consisting of stem + ing were more common in children with DLD than those with TD in the novel verb condition.DiscussionContrary to an earlier report (Jacobson & Schwartz, 2005), the relative greater difficulty with regular and novel verbs was replaced by greater difficulty for irregular past tense, a pattern consistent with monolingual impairment. Age was a contributing factor, particularly for younger children with DLD who produced more stem + ing errors in the novel verb condition. For all children, and particularly for those with DLD, an extended period for irregular past tense learning was evident. The results support a usage-based theory of language acquisition and impairment.

Consequences of Misspecifying the Error Covariance Structure in Linear Mixed Models for Longitudinal Data

Methodology ◽  
2008 ◽  
Vol 4 (1) ◽  
pp. 10-21 ◽  
Author(s):  
Guillermo Vallejo ◽  
Manuel Ato ◽  
Tamara Valdés
Keyword(s):  
Longitudinal Data ◽  
Repeated Measures ◽  
Fixed Effects ◽  
Error Control ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Covariance Structure ◽  
Correct Selection ◽  
Type I ◽  
Negative Consequences

Abstract. Repeated measures and longitudinal data are frequently analyzed using a linear mixed model. According to this approach, rather than presuming a certain type of covariance structure analysts choose the model that best describes their data prior to carrying out inferences of interest. Because it is not possible to know the underlying covariance structure in advance, researchers often use fit criteria to select from possible covariance structures. SAS Institute's (2004) Proc Mixed program, allows users to model the correct covariance structure by comparing Akaike's Information Criterion (AIC), Hurvich and Tsai's Criterion (AICC), Schwarz's Bayesian Criterion (BIC), Bozdogan's Criterion (CAIC), and Hannan and Quinn's Criterion (HQIC). Monte Carlo methods are used to examine performance of these criteria. The program also investigated the effects of misspecification on properties of the inferences. The results of the simulation show that neither criterion always lead to correct selection of model and that misspecification has negative consequences on estimates of standard errors of linear combinations and tests. When data were generated from symmetric distributions, the best AIC model generally provided robust Type I error control for tests of fixed effects. However, when data were generated from distributions with moderate or severe skewness, neither criterion provided valid tests.

Long-term seizure outcomes after pediatric temporal lobectomy: does brain MRI lesion matter?

2019 ◽  
Vol 24 (2) ◽  
pp. 200-208
Author(s):  
Ravindra Arya ◽  
Francesco T. Mangano ◽  
Paul S. Horn ◽  
Sabrina K. Kaul ◽  
Serena K. Kaul ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Hippocampal Sclerosis ◽  
Brain Mri ◽  
Temporal Lobectomy ◽  
Seizure Freedom ◽  
Seizure Onset

OBJECTIVEThere is emerging data that adults with temporal lobe epilepsy (TLE) without a discrete lesion on brain MRI have surgical outcomes comparable to those with hippocampal sclerosis (HS). However, pediatric TLE is different from its adult counterpart. In this study, the authors investigated if the presence of a potentially epileptogenic lesion on presurgical brain MRI influences the long-term seizure outcomes after pediatric temporal lobectomy.METHODSChildren who underwent temporal lobectomy between 2007 and 2015 and had at least 1 year of seizure outcomes data were identified. These were classified into lesional and MRI-negative groups based on whether an epilepsy-protocol brain MRI showed a lesion sufficiently specific to guide surgical decisions. These patients were also categorized into pure TLE and temporal plus epilepsies based on the neurophysiological localization of the seizure-onset zone. Seizure outcomes at each follow-up visit were incorporated into a repeated-measures generalized linear mixed model (GLMM) with MRI status as a grouping variable. Clinical variables were incorporated into GLMM as covariates.RESULTSOne hundred nine patients (44 females) were included, aged 5 to 21 years, and were classified as lesional (73%), MRI negative (27%), pure TLE (56%), and temporal plus (44%). After a mean follow-up of 3.2 years (range 1.2–8.8 years), 66% of the patients were seizure free for ≥ 1 year at last follow-up. GLMM analysis revealed that lesional patients were more likely to be seizure free over the long term compared to MRI-negative patients for the overall cohort (OR 2.58, p < 0.0001) and for temporal plus epilepsies (OR 1.85, p = 0.0052). The effect of MRI lesion was not significant for pure TLE (OR 2.64, p = 0.0635). Concordance of ictal electroencephalography (OR 3.46, p < 0.0001), magnetoencephalography (OR 4.26, p < 0.0001), and later age of seizure onset (OR 1.05, p = 0.0091) were associated with a higher likelihood of seizure freedom. The most common histological findings included cortical dysplasia types 1B and 2A, HS (40% with dual pathology), and tuberous sclerosis.CONCLUSIONSA lesion on presurgical brain MRI is an important determinant of long-term seizure freedom after pediatric temporal lobectomy. Pediatric TLE is heterogeneous regarding etiologies and organization of seizure-onset zones with many patients qualifying for temporal plus nosology. The presence of an MRI lesion determined seizure outcomes in patients with temporal plus epilepsies. However, pure TLE had comparable surgical seizure outcomes for lesional and MRI-negative groups.

scholarly journals Mood and Global Symptom Changes among Psychotherapy Clients with Depressive Personality

2012 ◽  
Vol 2012 ◽  
pp. 1-12
Author(s):  
Rachel E. Maddux ◽  
Lars-Gunnar Lundh
Keyword(s):  
Repeated Measures ◽  
Mixed Model ◽  
Psychological Symptoms ◽  
Self Report ◽  
Treatment Results ◽  
Repeated Measures Analysis ◽  
Depressive Personality ◽  
Symptom Changes ◽  
Psychotherapy Clients ◽  
Over Time

The present study assessed the rate of depressive personality (DP), as measured by the self-report instrument depressive personality disorder inventory (DPDI), among 159 clients entering psychotherapy at an outpatient university clinic. The presenting clinical profile was evaluated for those with and without DP, including levels of depressed mood, other psychological symptoms, and global severity of psychopathology. Clients were followed naturalistically over the course of therapy, up to 40 weeks, and reassessed on these variables again after treatment. Results indicated that 44 percent of the sample qualified for DP prior to treatment, and these individuals had a comparatively more severe and complex presenting disposition than those without DP. Mixed-model repeated-measures analysis of variance was used to examine between-groups changes on mood and global severity over time, with those with DP demonstrating larger reductions on both outcome variables, although still showing more symptoms after treatment, than those without DP. Only eleven percent of the sample continued to endorse DP following treatment. These findings suggest that in routine clinical situations, psychotherapy may benefit individuals with DP.

scholarly journals Joint modeling of multiple repeated measures and survival data using multidimensional latent trait linear mixed model

2018 ◽  
Vol 28 (10-11) ◽  
pp. 3392-3403 ◽  
Author(s):  
Jue Wang ◽  
Sheng Luo
Keyword(s):  
Survival Data ◽  
Repeated Measures ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Proportional Hazards Model ◽  
Latent Trait ◽  
Joint Modeling ◽  
Fine Motor ◽  
Terminal Event ◽  
Longitudinal Outcomes

Impairment caused by Amyotrophic lateral sclerosis (ALS) is multidimensional (e.g. bulbar, fine motor, gross motor) and progressive. Its multidimensional nature precludes a single outcome to measure disease progression. Clinical trials of ALS use multiple longitudinal outcomes to assess the treatment effects on overall improvement. A terminal event such as death or dropout can stop the follow-up process. Moreover, the time to the terminal event may be dependent on the multivariate longitudinal measurements. In this article, we develop a joint model consisting of a multidimensional latent trait linear mixed model (MLTLMM) for the multiple longitudinal outcomes, and a proportional hazards model with piecewise constant baseline hazard for the event time data. Shared random effects are used to link together two models. The model inference is conducted using a Bayesian framework via Markov chain Monte Carlo simulation implemented in Stan language. Our proposed model is evaluated by simulation studies and is applied to the Ceftriaxone study, a motivating clinical trial assessing the effect of ceftriaxone on ALS patients.

Effects of a Combination of Stances and Points of Aim on Putting Accuracy

1988 ◽  
Vol 66 (1) ◽  
pp. 139-143 ◽  
Author(s):  
Erich Gott ◽  
Carl Mc Gown
Keyword(s):  
Analysis Of Variance ◽  
Repeated Measures ◽  
Traditional Method ◽  
Constant Error ◽  
Popular Opinion ◽  
Variable Error ◽  
Repeated Measures Analysis ◽  
Better Than

The purpose of this study was to determine the effects of two putting stances (conventional versus side-saddle) and two points of aim (ball versus hole) on putting accuracy. Subjects (12 men, 4 women) were taught to putt using four methods: (a) conventional stance, eyes on the ball; (b) conventional stance, eyes on the hole; (c) side-saddle stance, eyes on the ball; and (d) side-saddle stance, eyes on the hole. Each subject practiced each method for 2 wk., after which they were tested for purring accuracy by counting putts made, determining constant error, and by calculating variable error. Accuracy was assessed at 5 and 15 ft. A 2 by 2 repeated-measures analysis of variance showed that there was no single combination of stance and point of aim that was significantly better than another at either distance. This suggests that, contrary to popular opinion, the traditional method of putting is not the best method for putting; other methods are equally as good and could be used if individually desired.

scholarly journals Estimating Bayes factors from minimal summary statistics in repeated measures analysis of variance designs

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Thomas Faulkenberry
Keyword(s):  
Analysis Of Variance ◽  
Repeated Measures ◽  
Bayes Factor ◽  
Linear Models ◽  
Repeated Measurements ◽  
Bayes Factors ◽  
Complex Method ◽  
Summary Statistics ◽  
Minimal Set ◽  
Repeated Measures Analysis

In this paper, I develop a formula for estimating Bayes factors directly from minimal summary statistics produced in repeated measures analysis of variance designs. The formula, which requires knowing only the F-statistic, the number of subjects, and the number of repeated measurements per subject, is based on the BIC approximation of the Bayes factor, a common default method for Bayesian computation with linear models. In addition to providing computational examples, I report a simulation study in which I demonstrate that the formula compares favorably to a recently developed, more complex method that accounts for correlation between repeated measurements. The minimal BIC method provides a simple way for researchers to estimate Bayes factors from a minimal set of summary statistics, giving users a powerful index for estimating the evidential value of not only their own data, but also the data reported in published studies.

Sign in / Sign up

Export Citation Format

Share Document