USING STEPWISE MULTIPLE REGRESSION MODELS TO PREDICT BODY WEIGHT AND SOME CARCASS TRAITS FROM SOME BODY MEASUREMENTS AT EARLY AGE IN TURKEYS

2014 ◽  
Vol 34 (3) ◽  
pp. 809-830
Keyword(s):  
Body Weight ◽  
Multiple Regression ◽  
Regression Models ◽  
Carcass Traits ◽  
Stepwise Multiple Regression ◽  
Early Age ◽  
Body Measurements ◽  
Predict Body Weight ◽  
Multiple Regression Models

Social Deprivation and Rates of Treated Mental Disorder

1991 ◽  
Vol 158 (4) ◽  
pp. 475-484 ◽  
Author(s):  
Graham Thornicroft
Keyword(s):  
Multiple Regression ◽  
Regression Models ◽  
Social Deprivation ◽  
Psychiatric Morbidity ◽  
Living Alone ◽  
Stepwise Multiple Regression ◽  
Psychiatric Admission ◽  
Admission Rates ◽  
Multiple Regression Models ◽  
High Degree

A review of the literature shows that there are strong associations of treated prevalence rates of psychiatric disorder with social class, sex, marital status, ethnic group and living alone; and moderate associations with living in inner-city areas and a high degree of residential mobility. The Jarman-8 index of social deprivation correlates with psychiatric admission rates for patients aged less than 65 years (R2–0.38). Individual census variables can themselves account for up to 0.71 of the variance in the admission rates, while combined in a stepwise multiple regression the census variables will account for over 0.95 of this variation. Multiple regression models using individual census variables and derived indices should be applied next on a wider geographical basis, and to narrower age, sex and diagnosis-specific psychiatric morbidity rates.

scholarly journals Predicting Body Weight of Ethiopian Indigenous Chicken Populations from Morphometric Measurements

2021 ◽  
Vol 9 (6) ◽  
pp. 1138-1143
Author(s):  
Fikrineh Negash
Keyword(s):  
Body Weight ◽  
Multiple Regression ◽  
Correlation Coefficients ◽  
Stepwise Multiple Regression ◽  
Regression Equations ◽  
Body Measurements ◽  
Indigenous Chicken ◽  
Morphometric Measurements ◽  
Measuring Tape ◽  
The Relationship

The purpose of this study was to estimate the relationship between body weight (BW) and morphometric measurements of Ethiopian indigenous chicken populations and to develop prediction equations used to estimate BW from body measurements. A total of 621 chickens comprising 134 males and 487 females reared under smallholder management conditions were used for the study. Body weight and morphometric measurements including body length (BL), chest circumference (CC), shank length (SL), and shank circumference (SC) were taken using a hanging scale and a textile measuring tape, respectively. The relationship between BW and morphometric measurements was determined using Pearson’s correlation coefficients (r) and stepwise multiple regression analyses. Descriptive statistics indicated that male birds were heavier than female birds. Correlation results revealed that body weight was significantly and strongly correlated with SL (r = 0.76) in both sexes, and moderately correlated with SC (r = 0.69), BL (r = 0.67), and CC (r = 0.52) in male birds, BL (r=0.68) and SC (r = 0.59) in female birds. Compared to other measurements, SL best predicted BW in both male and female birds, with coefficients of determination (R2) = 0.58. Combining SL with other body measurements (BL, CC, and SC) generally improved the predictive power of the equation. Thus, multiple regression equations that included a combination of the four linear body measurements are more suitable for predicting BW of Ethiopian indigenous chicken populations.

scholarly journals 242 Effect of trucking distance on sale price of beef calf and feeder cattle lots sold through video auctions from 2010 through 2018

2020 ◽  
Vol 98 (Supplement_3) ◽  
pp. 10-11
Author(s):  
Esther D McCabe ◽  
Mike E King ◽  
Karol E Fike ◽  
Maggie J Smith ◽  
Glenn M Rogers ◽  
...  
Keyword(s):  
Multiple Regression ◽  
Regression Models ◽  
Average Weight ◽  
Sale Price ◽  
Feeder Cattle ◽  
A Value ◽  
Multiple Regression Models ◽  
Determine Effect

Abstract The objective was to determine effect of trucking distance on sale price of beef calf and feeder cattle lots sold through Superior Livestock Video Auctions from 2010 through 2018. Data analyzed were collected from 211 livestock video auctions. There were 42,043 beef calf lots and 19,680 feeder cattle lots used in these analyses. Six states (Colorado, Iowa, Kansas, Nebraska, Oklahoma, and Texas) of delivery comprised 70% of calf lots and 83% of feeder cattle lots and were used in these analyses. All lot characteristics that could be accurately quantified or categorized were used to develop multiple regression models that evaluated effects of independent factors using backwards selection. A value of P < 0.05 was used to maintain a factor in the final models. Based upon reported state of origin and state of delivery, lots were categorized into one of the following trucking distance categories: 1) Within-State, 2) Short-Haul, 3) Medium-Haul, and 4) Long-Haul. Average weight and number of calves in lots analyzed was 259.2 ± 38.4 kg BW and 100.6 ± 74.3 head, respectively. Average weight and number of feeder cattle in lots analyzed was 358.4 ± 34.3 kg BW and 110.6 ± 104.1 head, respectively. Beef calf lots hauled Within-State sold for more ($169.24/45.36 kg; P < 0.0001) than other trucking distance categories (Table 1). Long-Haul calf lots sold for the lowest (P < 0.0001) price ($166.70/45.36 kg). Within-State and Short-Haul feeder cattle lots sold for the greatest (P < 0.0001) price ($149.96 and $149.81/45.36 kg, respectively; Table 2). Long-Haul feeder cattle lots sold for the lowest (P < 0.0001) price, $148.43/45.36 kg. These results indicate there is a price advantage for lots expected to be hauled shorter distances, likely because of cost and risk associated with transportation.

Multiple regression models for predicting total daily pollen concentration in Cartagena

Grana ◽  
2005 ◽  
Vol 44 (2) ◽  
pp. 108-114 ◽  
Author(s):  
José Manuel Angosto ◽  
Stella Moreno‐Grau ◽  
Javier Bayo ◽  
Belén Elvira‐Rendueles
Keyword(s):  
Multiple Regression ◽  
Regression Models ◽  
Pollen Concentration ◽  
Multiple Regression Models ◽  
Daily Pollen Concentration

Abstract WP238: Atrial Fibrillation is Associated With Severe Basal Ganglia Perivascular Spaces

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Alvin S Das ◽  
Elif Gokcal ◽  
Robert W Regenhardt ◽  
Andrew Warren ◽  
Kristin Schwab ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Basal Ganglia ◽  
Multiple Regression ◽  
Regression Models ◽  
Small Vessel Disease ◽  
Perivascular Spaces ◽  
Nonvalvular Atrial Fibrillation ◽  
Related Factors ◽  
Multiple Regression Models ◽  
Independent Effects

Introduction: High burdens of basal ganglia-perivascular spaces (BG-PVS) are often attributed to underlying hypertensive cerebral small vessel disease (HTN-CSVD). Although PVS are thought to arise from decreased perivascular drainage related to changes in arterial pulsatility, the contribution of pulsatility changes from nonvalvular atrial fibrillation (NVAF) has not been studied. Hypothesis: We hypothesized that NVAF patients have a higher burden of BG-PVS than HTN-CSVD patients, possibly through hemodynamic factors related to NVAF. Methods: Through an observational single-center study of consecutive stroke patients, we compared BG-EPVS severity between 136 patients with NVAF-related ischemic stroke (NVAF-IS) and 107 patients with HTN-CSVD-related intracerebral hemorrhage (HTN-ICH) without NVAF. Within the NVAF cohort, we also built multiple regression models to evaluate independent effects of NVAF-related factors on BG-PVS. All multiple regression models were adjusted for age, hypertension, sex, and neuroimaging markers of CSVD (extent of white matter hyperintensities (WMH), presence of lacunes, and cerebral microbleeds). Results: Patients with NVAF-IS were older than patients with HTN-ICH (75 + 12 vs. 64 + 13, p < 0.0001); however, there was no difference in sex between groups ( p = 0.6). Severe BG-PVS (defined as > 20 PVS in the BG) were found in 42.6% of NVAF-IS patients vs. 8.4% of HTN-ICH ( p < 0.0001). Even after multivariate adjustment, the presence of NVAF remained significantly related to BG-PVS ( p = 0.001). Within the NVAF cohort, CHA2DS2-VASc was associated with the presence of severe BG-PVS ( p = 0.003) despite controlling for other covariates. When CHA2DS2-VASc was replaced with its individual components in the same regression model, congestive heart failure (CHF, p = 0.017), WMH burden ( p = 0.009), and age ( p = 0.02) were found to be predictors of severe BG-PVS. Conclusions: Severe BG-PVS were significantly more common in NVAF patients compared to HTN-CSVD patients. NVAF-related features (CHA2DS2-VASc score) and CHF were associated with higher burdens of BG-PVS. These findings suggest that NVAF might play a role in the development of BG-PVS, conceivably through hemodynamic factors.

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