Conservative sample size for multiple regression models

2021 ◽  
pp. 1-7
Author(s):  
Matthew J. McIntosh
Keyword(s):  
Sample Size ◽  
Multiple Regression ◽  
Regression Models ◽  
Multiple Regression Models

scholarly journals Fine-Scale Mapping of Quantitative Trait Loci Using Historical Recombinations

Genetics ◽  
1997 ◽  
Vol 145 (4) ◽  
pp. 1201-1218
Author(s):  
Momiao Xiong ◽  
Sun-Wei Guo
Keyword(s):  
Qtl Mapping ◽  
Regression Model ◽  
Sample Size ◽  
Multiple Regression ◽  
Regression Models ◽  
Fine Scale ◽  
Simple Regression Model ◽  
Multiple Regression Models ◽  
Qtl Map ◽  
Simple Regression

With increasing popularity of QTL mapping in economically important animals and experimental species, the need for statistical methodology for fine-scale QTL mapping becomes increasingly urgent. The ability to disentangle several linked QTL depends on the number of recombination events. An obvious approach to increase the recombination events is to increase sample size, but this approach is often constrained by resources. Moreover, increasing the sample size beyond a certain point will not further reduce the length of confidence interval for QTL map locations. The alternative approach is to use historical recombinations. We use analytical methods to examine the properties of fine QTL mapping using historical recombinations that are accumulated through repeated intercrossing from an F2 population. We demonstrate that, using the historical recombinations, both simple and multiple regression models can reduce significantly the lengths of support intervals for estimated QTL map locations and the variances of estimated QTL map locations. We also demonstrate that, while the simple regression model using historical recombinations does not reduce the variances of the estimated additive and dominant effects, the multiple regression model does. We further determine the power and threshold values for both the simple and multiple regression models. In addition, we calculate the Kullback-Leibler distance and Fisher information for the simple regression model, in the hope to further understand the advantages and disadvantages of using historical recombinations relative to F2 data.

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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