scholarly journals Designs involving sequences of treatments with residuals proportional to direct effects

2021 ◽  
Author(s):  
Cini Varghese ◽  
Seema Jaggi ◽  
Eldho Varghese ◽  
Mohd Harun ◽  
Devendra Kumar
Keyword(s):  
Empirical Study ◽  
Residual Effects ◽  
Experimental Unit ◽  
Direct Effects ◽  
Carryover Effects ◽  
Maximum Information ◽  
Popular Classes ◽  
New Treatment ◽  
Unit Period

Designs involving sequences of treatments are advantageously used when observations are taken repeatedly from same experimental unit period after period as a new treatment is applied in each period. Hence, inclusion of residual effects into the model becomes the most important feature of such designs. Six popular classes of designs involving sequences of treatments are studied under a model with carryover effects proportional to the direct effects where the unknown proportionality parameter assumed values from -1 to +1. The objective of this empirical study was to determine the value of proportionality parameter for which maximum information can be drawn from the design.

A Statistical Analysts of Serially Balanced Sequences: First Order Residuals Proportional to Direct Effects

1986 ◽  
Vol 35 (1-2) ◽  
pp. 31-36 ◽  
Author(s):  
Mausumi Sen ◽  
Bikas K. Sinha
Keyword(s):  
Direct Effect ◽  
Residual Effect ◽  
Residual Effects ◽  
Experimental Unit ◽  
Direct Effects ◽  
First Order ◽  
Balanced Sequences

We consider the situation where a number of treatments are successively applied to a single experimental unit with both the direct effect of a treatment (in the period it is applied) and its residual effect (in the following period) being considered as two separate components of variation. We specialize to the case where the residual effects are certain known/unknown fractions of the correeponding direct effects. We discuss a method of analysis of the underlying data and also present various related results.

scholarly journals Yeast extract plus blood plasma in diets for piglets from 36 to 60 days old

2016 ◽  
Vol 46 (6) ◽  
pp. 1107-1112
Author(s):  
Cinthia Maria Carlos Pereira ◽  
Juarez Lopes Donzele ◽  
Rita Flávia Miranda de Oliveira Donzele ◽  
Charles Kiefer ◽  
Verônica Maria Pereira Bernardino ◽  
...  
Keyword(s):  
Blood Plasma ◽  
Yeast Extract ◽  
Control Diet ◽  
Residual Effect ◽  
Residual Effects ◽  
Daily Weight Gain ◽  
Feed Consumption ◽  
Experimental Unit ◽  
Feed Conversion ◽  
Performance Variables

ABSTRACT: To evaluate inclusion levels and residual effects of diets containing yeast extract (YE) plus blood plasma (BP) on the performance of 36 to 60-days old piglets, 105 piglets were used (8.75±0.72kg), and they were distributed under a randomized block experimental design with five treatments (control - 2.0% BP; 1.0% BP plus 0.0, 1.0, 2.0, or 3.0% YE), seven repetitions, and three animals per experimental unit. Piglets were given experimental diets from 36 to 49 days of age. From 50 to 60 day of age, all piglets received the same diet. No effects from treatments (P>0.10) were observed on the performance variables from 36 to 49 day of age. From 50 to 60 day of age, an effect was observed from YE levels on the daily feed consumption (P<0.03), daily weight gain (p<0.01), and final weight (P<0.06), which increased quadratically up to 1.67, 1.67, and 1.55% YE levels, respectively. Piglets which were fed with the diet containing 1.0% BP + 2.0% YE were observed to have better feed conversion ratios (P<0.01) as compared to the control diet (2.0% BP). As it provides a better residual effect, the inclusion of 1.67% yeast extract may replace 50% of blood plasma in 36 to 49-days old piglet diets.

scholarly journals Path analysis of yield components in tropical pumpkin

1969 ◽  
Vol 90 (3-4) ◽  
pp. 183-191
Author(s):  
Miguel Espitia-Camacho ◽  
Franco A. Vallejo-Cabrera ◽  
Diosdado Baena-Garcia ◽  
Linda Wessel-Beaver
Keyword(s):  
Path Analysis ◽  
Indirect Effects ◽  
Block Design ◽  
Genetic Correlations ◽  
Fruit Weight ◽  
Residual Effects ◽  
Path Coefficient ◽  
Direct Effects ◽  
Randomized Complete Block Design ◽  
Effect On Yield

Path coefficient analysis was carried out in tropical pumpkin (Cucurbita moschata Duchesne) for yield per plant as a function of number of fruit per plant and weight per fruit, using phenotypic and genetic correlations from two diallels: one using five varieties (variety diallel) and a second using five S1 lines derived from the varieties (line diallel). A randomized complete block design with five replications was used to evaluate 15 genotypes from each diallel, not including reciprocals. Direct effects were 300 to 500% greater than indirect effects in the line diallel. In contrast, direct effects were only 17 to 68% greater than indirect effects in the variety diallel. Effects (direct and indirect) were greater (17 to 500%) when genetic correlations rather than phenotype correlations (42 to 440%) were used in the path analysis. Fruit weight showed a greater effect on yield than did number of fruit, with values between 3.2 to 4.9 times the residual effects. Fruit weight and number of fruit can be used as selection criteria to increase yield in tropical pumpkin.  

scholarly journals RESIDUAL ACTIVITY OF HERBICIDES APPLIED TO COTTON ON CROPS CULTIVATED IN SUCCESSION

2016 ◽  
Vol 29 (1) ◽  
pp. 143-152 ◽  
Author(s):  
ELIEZER ANTONIO GHENO ◽  
RUBEM SILVÉRIO DE OLIVEIRA JUNIOR ◽  
JAMIL CONSTANTIN ◽  
HUDSON KAGUEYAMA TAKANO ◽  
ALEXANDRE GEMELLI
Keyword(s):  
Residual Activity ◽  
The Other ◽  
Residual Effects ◽  
Herbicide Application ◽  
Carryover Effects ◽  
Control Applications ◽  
Significant Damage ◽  
Crop Development ◽  
Herbicide Treatments ◽  
Time Periods

ABSTRACT: Herbicides with high persistence in soil can cause problems for crops sown in succession to their application. Thus, the aim of this study was to estimate, in greenhouse conditions, the safe period of time after application of preemergent herbicides used on cotton crops (isolated or in mixtures) for the crops grown in succession (bean, corn, and soybean). The experimental design was completely randomized in a factorial scheme (5 x 11) + 1, with five repetitions. For each experiment, treatments combined different time periods between herbicide application and sowing of crops (280, 210, 140, 70, and 0 days before sowing of crops) with eleven herbicide treatments: fomesafen (625 g ha-1) prometryne (1250 g ha-1), diuron (1250 g ha-1), S-metolachlor (768 g ha-1), clomazone (1000 g ha-1), fomesafen + prometryne (625 + 1250 g ha-1), fomesafen + diuron (625 + 1250 g ha-1), fomesafen + S-metolachlor (625 + 768 g ha-1), fomesafen + clomazone (625 + 1000 g ha-1), fomesafen + clomazone + diuron (625 + 1000 + 1250 g ha-1), and fomesafen + clomazone + prometryne (625 + 1000 + 1250 g ha-1), plus an untreated control. Applications of diuron showed the greatest persistence, causing the largest carryover effects for the three crops evaluated. The other treatments showed residual effects or affected crop development when sowings were performed up to 70 days after application. At later periods no significant damage was observed.

Experimental Designs Balanced for the Estimation of Residual Effects of Treatments

1949 ◽  
Vol 2 (2) ◽  
pp. 149 ◽  
Author(s):  
EJ Williams
Keyword(s):  
Residual Effect ◽  
Latin Squares ◽  
Experimental Designs ◽  
Residual Effects ◽  
Direct Effects ◽  
Balanced Design ◽  
Orthogonal Latin Squares ◽  
Mutually Orthogonal Latin Squares ◽  
Wide Applicability ◽  
Balanced Designs

Where an experiment can be carried out by applying different treatments in succession to the same unit of experimental material, accurate comparisons can be made between the effects of different treatments. To allow for the residual effect of previous treatments on the result obtained for any given treatment, it is desirable to adjust the results for such effects. Methods of constructing balanced designs for the estimation of these residual effects are described in this paper, and are summarized as follows. Designs balanced for effect of single preceding treatment: When n, the number of treatments, is even, a balanced design is possible with n replications ; when n is odd, 2n replications are required.Designs balanced for the effects of any number of preceding treatments, ignoring the interaction of residual effects: When n is a prime or a power of a prime, a balanced design is possible in n(n-1) replications, which may be set out as a set of n-1 mutually orthogonal Latin squares, with the same first columns. Designs which are not expressible as mutually orthogonal Latin squares are also possible. Designs balanced for the effect of the two preceding treatments and their interactions : A design can be developed from a set of n-l mutually orthogonal Latin squares obeying certain restrictions. The method of analysis of designs of this type is set out in detail, together with a numerical example. Direct effects of treatments are shown to be only slightly confounded, the maximum confounding being 4 per cent., when there are three treatments. These designs have wide applicability wherever successive treatments can be applied to the same unit of experimental material.

scholarly journals Correlations between Some Horticultural Traits in Walnut

HortScience ◽  
2010 ◽  
Vol 45 (11) ◽  
pp. 1690-1694 ◽  
Author(s):  
Reza Amiri ◽  
Kourosh Vahdati ◽  
Somayeh Mohsenipoor ◽  
Mohammad Reza Mozaffari ◽  
Charles Leslie
Keyword(s):  
Stepwise Regression ◽  
Important Determinant ◽  
Kernel Weight ◽  
Residual Effects ◽  
Direct Effects ◽  
Horticultural Traits ◽  
Dependent Variables ◽  
Independent Variable ◽  
Positive Direct ◽  
Leafing Date

Correlation and causal relationships among 21 horticultural traits were determined using 71 walnut genotypes selected from seven valleys in Kerman Province, Iran. Pearson's correlation coefficient was calculated. Kernel percentage and blight susceptibility were used as dependent variables in a stepwise regression model to determine predictor variables. Direct and indirect effects of each independent variable were calculated using path analysis. A highly significant correlation was observed between lateral bearing habit and yield. Lateral-bearing trees were also more susceptible to blight and winter cold than terminal bearers. Kernel and nut weights, shell thickness, and difficulty of extracting kernel halves were the most important traits accounting for kernel variation. Kernel weight and difficulty extracting kernel halves had the strongest positive direct effects and nut weight the most negative. Flowering habit, nut shape, and leafing date had positive direct effects on blight susceptibility, but the large residual effects suggest there are other important determinant traits for blight susceptibility, which were not considered in this study.

scholarly journals Greenhouse and Landscape Growth of Tiger Lily Cultivars Following Flurprimidol Preplant Bulb Soaks

2013 ◽  
Vol 23 (6) ◽  
pp. 820-822 ◽  
Author(s):  
Jared Barnes ◽  
Brian Whipker ◽  
Wayne Buhler ◽  
Ingram McCall
Keyword(s):  
Plant Growth ◽  
Stem Elongation ◽  
Residual Effect ◽  
Residual Effects ◽  
Retail Sales ◽  
Carryover Effects ◽  
Height Control ◽  
White Tiger ◽  
Lilium Lancifolium ◽  
Differential Responses

Experiments were conducted to evaluate the appropriate concentration of flurprimidol for ‘Orange Tiger’ tiger lily (Lilium lancifolium), the persistence of residual effects the following year with ‘Orange Tiger’, and differences in flurprimidol’s effect between tiger lily cultivars. In Expt. 1 flurprimidol was applied as a preplant bulb soak to determine its efficacy on height control of ‘Orange Tiger’ tiger lily. Bulbs were hydrated in 17 °C water for 1 h, allowed to drain 1 h, given 10 min soaks of 0, 5, 10, 20, 40, 80, and 160 mg·L−1 flurprimidol, and then allowed to drain for 1 h before potting. In Expt. 2 ‘Orange Tiger’ tiger lilies from Expt. 1 were then planted into outdoor beds to evaluate residual carryover effects of flurprimidol. Expt. 3 involved comparison trials of ‘Pink Tiger’, ‘White Tiger’, and ‘Yellow Tiger’ tiger lilies to determine if cultivars responded differently to flurprimidol drenches. Flurprimidol at 10 to 20 mg·L−1 effectively controlled stem elongation of ‘Orange Tiger’. No residual effect of flurprimidol on ‘Orange Tiger’ plant growth was observed a year after application. Optimal concentrations of flurprimidol for ‘Pink Tiger’ and ‘White Tiger’ were 2 to 5 mg·L−1 and for ‘Yellow Tiger’ 20 to 30 mg·L−1. Results showed that preplant bulb soaks prevented excessive height and provided plants that were more suitable in height for retail sales. Differential responses of ‘Pink Tiger’, ‘White Tiger’, and ‘Yellow Tiger’ tiger lilies to flurprimidol indicate that trials are required to customize optimal concentrations for other cultivars.

scholarly journals How does consumer engagement evolve when brands post across multiple social media?

2021 ◽  
Author(s):  
Vasu Unnava ◽  
Ashwin Aravindakshan
Keyword(s):  
Social Media ◽  
Resource Allocation ◽  
Spillover Effects ◽  
The Other ◽  
Direct Effects ◽  
Consumer Engagement ◽  
Carryover Effects ◽  
Allocation Model ◽  
Social Media Platforms ◽  
The Empirical Analysis

AbstractBrands allocate their social media advertising across multiple platforms such as Facebook, Twitter, Instagram, and YouTube. Because consumers use multiple social media, brand communications on one platform could generate engagement within the same platform (direct effects) and potentially impact engagement with the brand on the other platforms (spillover effects). Additionally, past engagement with a post on a platform could sustain into the future, thereby improving the longevity of posts (carryover effects). These effects could also vary across platforms. Drawing on recent advertising literature, the authors propose and test differential carryover, spillover, and direct effects within and across social media. The empirical analysis indicates that these effects exist and are significant, supporting the propositions presented. The analysis provides generalizable guidelines to social media marketers on the effectiveness of the various platforms at sustaining a post and at creating direct and spillover effects across other platforms. Finally, the study also exemplifies a resource allocation model for brands to use when allocating their efforts across the various social media platforms to maximize both consumer engagement and the firm’s return on social media investment.

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