scholarly journals The role of incubator classification on performance of incubators in Kenya.

2021 ◽  
Vol 10 (6) ◽  
pp. 256-267
Author(s):  
Miriti Jane Kinya ◽  
Kenneth Lawrance Wanjau ◽  
Nyagweth Ebenezer Odeyo
Keyword(s):  
Fixed Effects ◽  
Selection Criteria ◽  
Primary Data ◽  
Cross Sectional ◽  
Mixed Effect ◽  
Study Objective ◽  
Mixed Effect Models ◽  
Random Slopes ◽  
Linear Mixed Effect Models

The study sought to assess the importance of classifying incubators based on the programs offered for optimum performance. Client selection criteria were assessed through three constructs namely: models that fit program goals, uniqueness of ideas, and standard selection tool. A mixed cross-sectional and causal design was adopted and a census was carried out targeting all the 51 incubators. Primary data was collected with an incubator program as a grouping/ cluster variable yielding a multilevel data structure with incubator centres nested in programs. Linear mixed effect models were fitted using Stata to assess the study objective taking into account the fixed effects for the incubator centre level (level-1) and random effects for the program level (level-2). The uniqueness of ideas was found to have a significant fixed effect on performance at level one while at level two, the study found significant random intercepts of incubator centre performance across the programs. Models that match program goals and standard selection tools were also found to have significant random slopes as level two random covariates in the model. Based on the findings of significant random slopes, the study concluded that incubator classification is key for client selection criteria and enhances incubator performance.

scholarly journals Mate Availability and Sexual Disgust

2020 ◽  
Author(s):  
Courtney L. Crosby ◽  
Patrick Durkee ◽  
Anna Sedlacek ◽  
David M. Buss
Keyword(s):  
Mate Choice ◽  
Mate Selection ◽  
Local Environment ◽  
Relationship Status ◽  
Mixed Effect ◽  
Mate Availability ◽  
Mixed Effect Models ◽  
Sexual Disgust ◽  
Linear Mixed Effect Models

Objective: One of the factors that sexual disgust should be calibrated to is the size of the mating pool. Previous research provides evidence that low mate availability affects perceptions related to mate choice. However, methodological shortcomings leave the role of sexual disgust in facilitating mate selection unclear. We will examine whether perceptions of mate availability explain variance in levels of sexual disgust towards potential mates.Methods: Participants (N = 1,000) will rate how sexually disgusting they find 60 potential mates that have previously been rated on attractiveness by a separate group of raters. We will measure participants’ perceptions of mate availability in their local environment, self-perceived attractiveness and mate value, and relevant control variables (e.g., age, relationship status). Results: We will use linear mixed effect models to examine (1) the association between sexual disgust towards potential mates and perceived mate availability; (2) the sex difference in sexual disgust; (3) the association between targets’ attractiveness and raters’ sexual disgust; and (4) whether perceived mate availability moderates the association between sexual disgust and targets’ attractiveness. Conclusions: This study will test perceptions of mate availability as an input into the calibration of sexual disgust. The results will clarify the magnitude of mate availability perceptions on mate choice.

scholarly journals Syntactic predictability modulates parafoveal processing of inflectional morphology: evidence from word n+1 in Russian

2020 ◽  
Author(s):  
Anastasia Anatol Stoops ◽  
Jack Dempsey ◽  
Kiel Christianson
Keyword(s):  
Test Score ◽  
Inflectional Morphology ◽  
Parafoveal Processing ◽  
Mixed Effect ◽  
Boundary Change ◽  
Word Level ◽  
Mixed Effect Models ◽  
Linear Mixed Effect Models ◽  
Cloze Test

We present the first investigation of parafoveal syntactic predictability modulation of inflectional morphology. Earlier eye-tracking studies with boundary-change manipulations have established that highly expected (78% Cloze test score) morphologically related preview have been integrated into the message level sentence stream as the related preview yielded preview cost over both the identical (no-change grammatical but less expected (22% Cloze test score)) and nonword previews (Stoops & Christianson, 2017; 2019). The current study reversed the syntactic expectations for the identical (94% Cloze test score) and related (ungrammatical 0% Cloze test score) previews and found only word-level facilitation of the ungrammatical related preview. Both frequentist and Bayesian linear mixed-effect models revealed that the related preview did not differ from identical in any of the measures and yielded a preview benefit over nonword previews in the total time. Further work is needed to understand the role of syntactic predictability on parafoveal processing in reading.

scholarly journals Role of temperature, influenza and other local characteristics in seasonality of mortality: a population-based time-series study in Japan

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e044876
Author(s):  
Lina Madaniyazi ◽  
Chris Fook Sheng Ng ◽  
Xerxes Seposo ◽  
Michiko Toizumi ◽  
Lay-Myint Yoshida ◽  
...  
Keyword(s):  
Time Series ◽  
Population Based ◽  
Mixed Effect ◽  
Respiratory Mortality ◽  
Local Characteristics ◽  
Mixed Effect Models ◽  
Before And After ◽  
Series Study ◽  
Linear Mixed Effect Models

ObjectivesTo investigate the extent to which temperature and influenza explained seasonality of mortality in Japan and to examine the association of the seasonality with prefecture-specific characteristics.DesignWe conducted time-series analysis to estimate the seasonal amplitude before and after adjusting for temperature and/or influenza-like illness (ILI). Next, we applied linear mixed effect models to investigate the association of seasonal amplitudes with each indicator on prefecture-specific characteristics on climate, demographic and socioeconomic factors and adaptations.Setting47 prefectures in JapanParticipantsDeaths for all-cause, circulatory, and respiratory disease between 1999 and 2015.Outcome measuresPeak-to-trough ratio (PTR, a measure of seasonal amplitude).ResultsThe nationwide unadjusted-PTRs for all-cause, circulatory and respiratory mortality were 1.29 (95% CIs: 1.28 to 1.31), 1.55 (95% CI: 1.52 to 1.57) and 1.45 (95% CI: 1.43 to 1.48), respectively. These PTRs reduced substantially after adjusting for temperature but very little after a separate adjustment for ILI. Furthermore, seasonal amplitudes varied between prefectures. However, there was no strong evidence for the associations of PTR with the indicators on prefecture-specific characteristics.ConclusionsSeasonality of mortality is primarily driven by temperature in Japan. The spatial variation in seasonal amplitudes was not associated with prefecture-specific characteristics. Although further investigations are required to confirm our findings, this study can help us gain a better understanding of the mechanisms underlying seasonality of mortality.

scholarly journals Test-Retest Variability of Relative Tracer Delivery Rate as Measured by [11C]PiB

2021 ◽  
Author(s):  
Fiona Heeman ◽  
Janine Hendriks ◽  
Isadora Lopes Alves ◽  
Nelleke Tolboom ◽  
Bart N. M. van Berckel ◽  
...  
Keyword(s):  
Delivery Rate ◽  
Intrinsic Variability ◽  
Reference Tissue ◽  
Cross Sectional ◽  
Mixed Effect ◽  
Mixed Effect Models ◽  
Retrospective Data Analysis ◽  
Simplified Reference Tissue Model ◽  
Pet Scans ◽  
Linear Mixed Effect Models

Abstract Purpose Moderate-to-high correlations have been reported between the [11C]PiB PET-derived relative tracer delivery rate R1 and relative CBF as measured using [15O]H2O PET, supporting its use as a proxy of relative CBF. As longitudinal PET studies become more common for measuring treatment efficacy or disease progression, it is important to know the intrinsic variability of R1. The purpose of the present study was to determine this through a retrospective data analysis. Procedures Test-retest data belonging to twelve participants, who underwent two 90 min [11C]PiB PET scans, were retrospectively included. The voxel-based implementation of the two-step simplified reference tissue model with cerebellar grey matter as reference tissue was used to compute R1 images. Next, test-retest variability was calculated, and test and retest R1 measures were compared using linear mixed effect models and a Bland-Altman analysis. Results Test-retest variability was low across regions (max. 5.8 %), and test and retest measures showed high, significant correlations (R2=0.92, slope=0.98) and a negligible bias (0.69±3.07 %). Conclusions In conclusion, the high precision of [11C]PiB R1 suggests suitable applicability for cross-sectional and longitudinal studies.

scholarly journals Specifying the random effect structure in linear mixed effect models for analyzing psycholinguistic data

Methodology ◽  
2020 ◽  
Vol 16 (2) ◽  
pp. 92-111
Author(s):  
Jungkyu Park ◽  
Ramsey Cardwell ◽  
Hsiu-Ting Yu
Keyword(s):  
Random Effect ◽  
Experimental Conditions ◽  
Mixed Effect ◽  
Linear Mixed Effect ◽  
Mixed Effect Models ◽  
Influential Paper ◽  
Within Subjects ◽  
Complex Models ◽  
Random Slopes ◽  
Linear Mixed Effect Models

Linear Mixed Effect Models (LMEM) have become a popular method for analyzing nested experimental data, which are often encountered in psycholinguistics and other fields. This approach allows experimental results to be generalized to the greater population of both subjects and experimental stimuli. In an influential paper Bar and his colleagues (2013; https://doi.org/10.1016/j.jml.2012.11.001) recommend specifying the maximal random effect structure allowed by the experimental design, which includes random intercepts and random slopes for all within-subjects and within-items experimental factors, as well as correlations between the random effects components. The goal of this paper is to formally investigate whether their recommendations can be generalized to wider variety of experimental conditions. The simulation results revealed that complex models (i.e., with more parameters) lead to a dramatic increase in the non-convergence rate. Furthermore, AIC and BIC were found to select the true model in the majority of cases, although selection accuracy varied by LMEM random effect structure.

scholarly journals A hierarchical bivariate meta-analysis of diagnostic test accuracy to provide direct comparisons of immunoassays vs. indirect immunofluorescence for initial screening of connective tissue diseases

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Michelle Elaine Orme ◽  
Carmen Andalucia ◽  
Sigrid Sjölander ◽  
Xavier Bossuyt
Keyword(s):  
Connective Tissue ◽  
Indirect Immunofluorescence ◽  
Meta Analysis ◽  
Connective Tissue Diseases ◽  
Test Accuracy ◽  
Initial Screening ◽  
Case Control Studies ◽  
Cross Sectional ◽  
Mixed Effect ◽  
Mixed Effect Models

AbstractObjectivesTo compare indirect immunofluorescence (IIF) for antinuclear antibodies (ANA) against immunoassays (IAs) as an initial screening test for connective tissue diseases (CTDs).MethodsA systematic literature review identified cross-sectional or case-control studies reporting test accuracy data for IIF and enzyme-linked immunosorbent assays (ELISA), fluorescence enzyme immunoassay (FEIA), chemiluminescent immunoassay (CLIA) or multiplex immunoassay (MIA). The meta-analysis used hierarchical, bivariate, mixed-effect models with random-effects by test.ResultsDirect comparisons of IIF with ELISA showed that both tests had good sensitivity (five studies, 2321 patients: ELISA: 90.3% [95% confidence interval (CI): 80.5%, 95.5%] vs. IIF at a cut-off of 1:80: 86.8% [95% CI: 81.8%, 90.6%]; p = 0.4) but low specificity, with considerable variance across assays (ELISA: 56.9% [95% CI: 40.9%, 71.5%] vs. IIF 1:80: 68.0% [95% CI: 39.5%, 87.4%]; p = 0.5). FEIA sensitivity was lower than IIF sensitivity (1:80: p = 0.005; 1:160: p = 0.051); however, FEIA specificity was higher (seven studies, n = 12,311, FEIA 93.6% [95% CI: 89.9%, 96.0%] vs. IIF 1:80 72.4% [95% CI: 62.2%, 80.7%]; p < 0.001; seven studies, n = 3251, FEIA 93.5% [95% CI: 91.1%, 95.3%] vs. IIF 1:160 81.1% [95% CI: 73.4%, 86.9%]; p < 0.0001). CLIA sensitivity was similar to IIF (1:80) with higher specificity (four studies, n = 1981: sensitivity 85.9% [95% CI: 64.7%, 95.3%]; p = 0.86; specificity 86.1% [95% CI: 78.3%, 91.4%]). More data are needed to make firm inferences for CLIA vs. IIF given the wide prediction region. There were too few studies for the meta-analysis of MIA vs. IIF (MIA sensitivity range 73.7%–86%; specificity 53%–91%).ConclusionsFEIA and CLIA have good specificity compared to IIF. A positive FEIA or CLIA test is useful to support the diagnosis of a CTD. A negative IIF test is useful to exclude a CTD.

Association of fine particulate matter with glucose and lipid metabolism: a longitudinal study in young adults

2021 ◽  
pp. oemed-2020-107039
Author(s):  
Jingyi Qin ◽  
Wei Xia ◽  
Gaodao Liang ◽  
Shunqing Xu ◽  
Xiuge Zhao ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Lipid Metabolism ◽  
Longitudinal Study ◽  
Fine Particulate Matter ◽  
Healthy Adults ◽  
Mixed Effect ◽  
Glucose And Lipid Metabolism ◽  
Mixed Effect Models ◽  
Fine Particulate ◽  
Linear Mixed Effect Models

ObjectivesThis study aimed to evaluate whether PM2.5 exposure in a highly polluted area (>100 µg/m3) affects glucose and lipid metabolism in healthy adults.MethodsWe recruited 110 healthy adults in Baoding city, Hebei, China, and followed them up between 2017 and 2018. Personal air samplers were used to monitor personal PM2.5 levels. Eight glucose and lipid metabolism parameters were quantified. We performed the linear mixed-effect models to investigate the relationships between PM2.5 and glucose and lipid metabolism parameters. Stratified analyses were further performed according to sex and body mass index (BMI).ResultsThe concentration of PM2.5 was the highest in spring, with a median of 232 μg/m3 and the lowest in autumn (139 μg/m3). After adjusting for potential confounders, we found that for each twofold increase in PM2.5, the median of insulin concentration decreased by 5.89% (95% CI −10.91% to −0.58%; p<0.05), and ox-LDL increased by 6.43% (95% CI 2.21% to 10.82%; p<0.05). Stratified analyses indicated that the associations were more pronounced in females, overweight and obese participants.ConclusionsExposure to high PM2.5 may have deleterious effects on glucose and lipid metabolism. Females, overweight and obese participants are more vulnerable.

scholarly journals Mediation by Organizational Design in the Influence of Organizational Ambidexterity on the Performance of Large Manufacturing Firms in Kenya

2020 ◽  
Vol 11 (4) ◽  
pp. 10
Author(s):  
Patrick M. Mutisya ◽  
Peter K'Obonyo ◽  
Kennedy Ogollah ◽  
James M. Njihia
Keyword(s):  
Organizational Performance ◽  
Organizational Design ◽  
Dynamic Capabilities ◽  
Manufacturing Firms ◽  
Primary Data ◽  
Organizational Ambidexterity ◽  
Cross Sectional ◽  
Mediating Role ◽  
Study Results

The aim of this study was to establish the role of organizational design in the organizational ambidexterity - performance relationship among large manufacturing firms (LMFs) in Kenya. The studies linking ambidexterity to organizational performance are few and with mixed findings. The few studies indicate that there is no clear ambidexterity - organizational performance relationship. The research was founded on dynamic capabilities and configurations theories. Based on the reviewed literature, a conceptual model and hypotheses were formulated. The study was guided by positivist philosophy. The population of the research was the entire 107 Kenyan large manufacturing firms (LMFs). Cross-sectional research design was used. Primary data in respect of predictor variables was used and was collected using a structured questionnaire. The respondents were the senior managers of the large manufacturing firms (LMFs) in Kenya; namely Chief Executive Officers/Managing Directors (CEOs/MDs) or General Managers (GMs), or Heads of departments (HODs). Descriptive statistics, correlations, linear, multiple and hierarchical regressions were applied in the data scrutiny and interpretation. The study results showed partial organizational design mediating role in the organizational ambidexterity - performance association of LMFs in Kenya. The study findings are useful to practitioners and managers of LMFs, policymakers in government as well as scholars and researchers. The study recommends further studies on the mediating role of organizational design, different variable operationalization, diversify respondents and context as well as longitudinal study.

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