scholarly journals THE EFFECT OF UNMEASURED CONFOUNDERS ON THE ABILITY TO ESTIMATE A TRUE PERFORMANCE OR SELECTION GRADIENT (AND OTHER PARTIAL REGRESSION COEFFICIENTS)

Evolution ◽  
2014 ◽  
Vol 68 (7) ◽  
pp. 2128-2136 ◽  
Author(s):  
Jeffrey A. Walker
Keyword(s):  
Regression Coefficients ◽  
Partial Regression ◽  
Selection Gradient ◽  
Unmeasured Confounders

COMPARISON OF OBSERVATIONS AND MACROCLIMATIC MODEL ESTIMATES OF MONTHLY WINTER SOIL TEMPERATURES AT OTTAWA

1985 ◽  
Vol 65 (1) ◽  
pp. 109-122 ◽  
Author(s):  
L. M. DWYER ◽  
H. N. HAYHOE
Keyword(s):  
Snow Cover ◽  
Predictive Models ◽  
Regression Models ◽  
Stepwise Regression ◽  
Regression Coefficients ◽  
Data Sets ◽  
Regression Equations ◽  
Grass Cover ◽  
Partial Regression ◽  
Soil Temperatures

Estimates of monthly soil temperatures under short-grass cover across Canada using a macroclimatic model (Ouellet 1973a) were compared to monthly averages of soil temperatures monitored over winter at Ottawa between November 1959 and April 1981. Although the fit between monthly estimates and Ottawa observations was generally good (R for all months and depths 0.10, 0.20, 0.50, 1.00 and 1.50 m was 0.90), it was noted that midwinter estimates were generally below observed temperatures at all soil depths. Data sets used in the development of the original Ouellet (1973a) multiple regression equations were collected from stations across Canada, many of which have reduced snow cover. It was found that the buffering capability of the snow cover accumulated at Ottawa during the winter months was underestimated by the pertinent partial regression coefficients in these equations. The coefficients were therefore modified for the Ottawa station during the winter months. The resultant regression models were used to estimate soil temperature during the winters of 1981–1982 and 1982–1983. Although the Ottawa-based models included fewer variables because of the smaller data base available from a single site, comparisons of model estimates and observations were good (R = 0.84 and 0.91) and midwinter estimates were not consistently underestimated as they were using the original Ouellet (1973a) model. Reliable monthly estimates of soil temperatures are important since they are a necessary input to more detailed predictive models of daily soil temperatures. Key words: Regression model, snowcover, stepwise regression, variable selection

506. The importance of machine milking rate in dairy cow management and breeding

1953 ◽  
Vol 20 (2) ◽  
pp. 138-145 ◽  
Author(s):  
F. H. Dodd ◽  
A. S. Foot
Keyword(s):  
Dairy Cows ◽  
Dairy Cow ◽  
Peak Flow ◽  
Milk Composition ◽  
Regression Coefficients ◽  
Partial Regression ◽  
Fat Percentage ◽  
Machine Milking ◽  
Lactation Length ◽  
The Relationship

An analysis has been carried out on the milk yield, milk composition and milking-rate records collected in one herd of dairy cows.It has been shown from the results of eighty-six heifers that for each pound per minute increase in inherent milking rate (i.e. peak flow) the standard lactation yield increases by 419 lb., the maximum daily yield by 0·9 lb., the lactation length by 8 days and the persistency index by 10 days, whilst the lactation solids-not-fat percentage decreases by 0·03 and the fat percentage by 0·04. All except the last coefficient were significant, although it was also shown that the relationship with solids-not-fat percentage was due to an interaction. Similarly, by the calculation of partial regression coefficients it was demonstrated that the relationship between milking rate and standard lactation yield was due to the effect of milking rate on maximum daily yield, lactation length and persistency.

The relationship between fall dormancy and germplasm source in North American alfalfa cultivars

1996 ◽  
Vol 76 (3) ◽  
pp. 429-433 ◽  
Author(s):  
D. T. Fairey ◽  
N. A. Fairey ◽  
L. P. Lefkovitch
Keyword(s):  
Genetic Diversity ◽  
Regression Analysis ◽  
Plant Height ◽  
North American ◽  
The Other ◽  
Regression Coefficients ◽  
Large Contribution ◽  
Partial Regression ◽  
Fall Dormancy ◽  
The Relationship

Most of the genetic diversity of North American alfalfa cultivars has been accounted for by nine germplasm sources listed in descending order of winter hardiness as follows: Medicago sativa ssp. falcata, Ladak, M. sativa ssp. xvaria, Turkistan, Flemish, Chilean, Peruvian, Indian and African. In most instances, the breeder assigns a fall dormancy score and the relative proportions of each of the nine germplasm source for each cultivar at registration. The fall dormancy score (1 = dormant to 9 = non-dormant), determined by measuring plant height in October after harvest in early September, is used to indicate cultivar adaptation for different regions. This study examines the relationship between germplasm composition and plant height, the equivalence of fall dormancy. The signs on the partial regression coefficients of a multiple regression analysis of plant height on the proportional content of the nine sources of germplasm showed that the fall dormancy fell essentially into two classes, namely, a dormant category, comprising cultivars containing a large contribution of Falcata and Ladak, and a non-dormant category, in which Indian and African germplasm predominate. This does not necessarily preclude the influence of any of the other germplasm sources on fall dormancy, since they represent a rich source of diversity. However, nine distinct classes were not recognisable, perhaps because of the lack of an exact equivalence between fall dormancy class and plant height of the fall regrowth. Since these observations have not been derived in a common nursery, the latitude and latitude × cultivar effects have been disregarded. These limitations should be recognized when using the currently assigned fall dormancy ratings to predict cultivar adaptation. Key words: Alfalfa, fall dormancy, sources of germplasm

scholarly journals The Opposing Effect of Hedonic and Eudaimonic Happiness on Gene Expression is Correlated Noise

2016 ◽  
Author(s):  
Jeffrey A. Walker
Keyword(s):  
Gene Expression ◽  
Fixed Effects ◽  
Regression Coefficients ◽  
Standard Errors ◽  
Type I ◽  
Correlated Noise ◽  
Partial Regression ◽  
Inflated Type ◽  
Opposing Effects ◽  
Eudaimonic Happiness

AbstractBackgroundThis paper presents a re-analysis of the gene set data from Fredrickson et al. 2013 and Fredrickson et al. 2015 which purportedly showed opposing effects of hedonic and eudaimonic happiness on the expression levels of a set of genes that have been correlated with social adversity. Fredrickson et al. 2015 used a linear model of fixed effects with correlated error (using GLS) to estimate the partial regression coefficients.MethodsThe standardized effects of hedonic and eudaimonic happiness on CTRA gene set expression estimated by GLS was compared to estimates using multivariate (OLS) linear models and generalized estimating equation (GEE) models. The OLS estimates were tested using a bootstrap t-test, O’Brien’s OLS test, a permutation t test, and the rotation z-test. The GEE estimates were tested using a Wald test with robust standard errors. The performance (type I, type II, and type M error) of all tests was investigated using a Monte Carlo simulation of data modeled after the 2015 dataset.ResultsStandardized OLS effects (mean partial regression coefficients) of Hedonia and Eudaimonia on gene expression levels are very small in both the 2013 and 2015 data, as well as the combined data.The p-values from all tests fail to reject any of the null models. The GEE estimates and tests are nearly identical to the OLS estimates and tests. By contrast, the GLS estimates are inconsistent between data sets, but in each dataset, at least one coefficient is large and highly statistically significant. The Monte Carlo simulation of error rates shows inflated type I error from the GLS test on data with a similar correlation structure to that in the 2015 dataset, and this error rate increases as the number of outcomes increases relative to the number of subjects. Bootstrap and permutation GLS distributions suggest that the GLS model not only results in downward biased standard errors but also inflated coefficients. Both distributions also show the expected, strong, negative correlation between the coefficients for Hedonia and Eudaimonia.DiscussionThe results fail to support opposing effects, or any detectable effect, of hedonic and eudaimonic well being on the pattern of gene expression. The apparently replicated pattern of hedonic and eudaimonic effects on gene expression is most parsimoniously explained as "correlated noise" due to the geometry of multiple regression. A linear mixed model for estimating fixed effects in designs with many repeated measures or outcomes should be used cautiously because of the potentially inflated type 1 and type M error.

scholarly journals Regression analysis of milk production traits in simmental cows

2011 ◽  
Vol 27 (4) ◽  
pp. 1433-1441
Author(s):  
M.D. Petrovic ◽  
V. Bogdanovic ◽  
M.M. Petrovic ◽  
S. Rakonjac
Keyword(s):  
Regression Analysis ◽  
Milk Production ◽  
Milk Fat ◽  
Regression Coefficients ◽  
Regression Equations ◽  
Production Traits ◽  
Milk Production Traits ◽  
Partial Regression ◽  
Three Generations ◽  
Lactation Length

The relationship between milk production traits over whole lactations was evaluated across three generations of Simmental cows, i.e. between daughters, dams and grand dams, by a phenotypic regression analysis with whole lactation traits in the daughter generation being used as the dependent variables (x1), and those in the dam and grand dam generations being used as the independent variables (x2 and x3). The results were obtained from a sample of 1170 daughters and as many dams and grand dams. The significance of the partial regression coefficients b2 and b3 was separately evaluated by a t-test. An analysis of variance was used to estimate the significance of the simultaneous effect of the production traits of dams and grand dams on the milk production achieved in the daughter generation. The calculated value of the partial regression coefficients for the whole lactation production traits across three generations (grand dams, dams and daughters) and their statistical significances determined by the t and F tests, as well as the regression equations used, suggested that the effect of the grand dam generation on the milk production traits in granddaughters was substantially lower than the effect of dams. The calculated partial regression coefficients (b2 and b3) were positive and statistically very significant (P<0.01), excepting the regression coefficients b3 for lactation length and b2 for milk fat content that were not statistically significant (P>0.05). A very significant change (P<0.01) was observed in all production traits in the daughter generation as simultaneously affected by the traits in the dam and grand dam generations.

Use of Soil Survey of England and Wales data bank (1950–1973) to summarize and establish relations between soil analyses, observed gley status and lithological contribution

1979 ◽  
Vol 92 (2) ◽  
pp. 383-391
Author(s):  
C. L. Bascomb ◽  
A. D. Todd
Keyword(s):  
Organic Matter ◽  
Predictive Power ◽  
Clay Content ◽  
Data Bank ◽  
Soil Survey ◽  
Regression Coefficients ◽  
Partial Regression ◽  
Parent Materials ◽  
Lithological Type ◽  
Clay Percentage

SummaryA statistical analysis is presented of published laboratory data on 4407 soil horizon samples collected by the Soil Survey of England and Wales during 1950–73, to typify soil taxa. Seventy-five percent of the profiles have fine textured parent materials in both calcareous and non-calcareous categories. Moderate to large increases in clay content down the profile, which could indicate argillio horizons, are found in 56% of the profiles but the influence of lithological discontinuities has not been eliminated. Argillic horizons are commonest on calcareous or low grade metamorphic rocks and non-calcareous clayey or silty sediments. Less than half the average frequency of clay increase between middle and bottom horizons is shown in the igneous and high grade metamorphic lithological type.pH gradient down the profile is not clearly related to altitude. The pH change (0·7) between top and bottom horizons in profiles from calcareous and igneous parent materials is twice as great as in other non-calcareous profiles. There is usually less clay in the top horizons than in others; the top horizon contains more than 35% clay about half as frequently as the lower horizons. Clay content categories have closely similar frequency in middle and bottom horizons. Gleying in horizon 1 is observed somewhat less frequently with increasing CaCO3. No consistent trend is found in the other horizons. Soil pH in 0·01 M-CaCl2 (pH8) is between 5·1 and 7·0 in 51% of all samples. pH5, values less than 4 occur in only 8% and are twice as common in top horizons (more than 5 cm thick) as in deeper ones. pH8, values greater than 7 are nearly twice as frequent (31%) in the bottom horizon as in the upper ones. Correlation of pH in water (pHw) with pH8 always exceeds 0·93 irrespective of lithological type. The difference of pHw from pH8 (δpH) calculated from the regression equation is 0·7–0·8 at pH6 values less than 4; it varies inversely with pH8, up to a value of 0·4–0·5 at pH6 greater than 7. Neutrality (pHw, 7) corresponds to pH8 6·5–6·6. There is no indication that δpH is related to altitude or gleying intensity but it varies according to lithological type by about 0·1 unit. Organic-matter content, as indicated by loss on ignition (950 °C) minus 10% of the measured clay percentage (LOIadj%) is little affected by lithological type; decrease with depth is steeper at pH8 less than 4 than at higher pH. Gleyed top horizons contain more organic matter than ungleyed; gradient down the profile is positively related to gleying intensity.The overall multiple regression of cation exchange capacity (CEC) on clay percentage and organic matter (LOIadj%) is (CEC = 1·21 + 0·40 clay% + 1·32 LOIadj), accounting for 61·4% of the total variance. When lithological types are considered separately the partial regression coefficients for clay percentages are greater in the two calcareous lithological types than in the non-calcareous. With lithological type 5 the large constant term and small coefficient of clay percentage indicate considerable contribution to CEC from particles or aggregates larger than 2 μm. Partial regression coefficients (lithological types 1–4 taken together), although similar both within horizon and within gley category are nevertheless shown to be significantly different. Within pH8 category, both partial regression coefficients increase directly with pH. Calculation of mean values of CEC on a clay basis for horizon 3, where contribution from organic matter is minimal, does not show significant differences between pH8 categories or gley categories.Although quantification of relationships has been possible, correlations are rarely high, so that predictive power is limited. Availability of soil group or subgroup categorizations using constant definitions based on objective measurements is suggested as a useful way of increasing predictive power within resulting smaller groups. The calculation of geographic (areal) distribution is probably the most useful purpose of a data bank of routine measurements, but the selection of samples to typify soil taxa used in this study would preclude such a use.

Paternal Association of Increased Susceptibility to Viral Haemorrhagic Septicaemia (VHS) in Rainbow Trout (Oncorhynchus mykiss)

1991 ◽  
Vol 48 (7) ◽  
pp. 1188-1191 ◽  
Author(s):  
P. Kaastrup ◽  
V. Hørlyck ◽  
N. J. Olesen ◽  
N. Lorenzen ◽  
P. E. Vestergaard Jørgensen ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
Oncorhynchus Mykiss ◽  
Regression Coefficients ◽  
Partial Regression ◽  
Haemorrhagic Septicaemia ◽  
Rainbow Trout Oncorhynchus Mykiss ◽  
Gynogenetic Offspring ◽  
Strain Dependent ◽  
Increased Susceptibility

Farming of rainbow trout (Oncorhynchus mykiss) in Europe is hampered by unacceptably heavy losses due to the severe infectious disease viral haemorrhagic septicaemia (VHS). Strain-dependent variation of VHS resistance exists. A long-term breeding programme to increase VHS resistance in rainbow trout has been started in Denmark. This programme will be based on experimental VHS challenge of the parental fish (n = 84) as well as their normal and gynogenetic offspring (16 fullsib F1 groups). We found a paternal influence on the average VHS resistance of the offspring; partial regression coefficients for sire-offspring were estimated at 0.30 ± 0.09 and for dam-offspring at −0.1 ± 0.12.

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