the joint effect of two variables acting together is called _____.

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A model in the form of y=Bo+B1Z1+B2Z2+ .. B2Z2 ...+ BpZp+z

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General linear model

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A test used to determine whether or not first order autocorrelation is present is:

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Durben Watson

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1/17 Created by Reality_Williams

Terms in this set (17)

A model in the form of y=Bo+B1Z1+B2Z2+ .. B2Z2 ...+ BpZp+z

General linear model

A test used to determine whether or not first order autocorrelation is present is:

Durben Watson

Which model can be used to accommodate curvilinear relationships between the independent variables and the dependent variables

Quadratic Model

The following model y+B0+B1x1+e is referred to as a

1st order model when you want have square term

In multiple regression analysis, the word linear in the term "general linear model" refers to the fact that

Bo B1 ext of ex of 1

Serial correlation is the same as

auto correlation

The joint effect of two variables acting together is called

interaction

A test to determine whether or not first order autocorrelation is present is:

durben watson test

Which of the following teat is used to determine whether an additional variable makes a significant contribution to a multiple regression model>

Parsal f test

A variable such as z whose value is z= x1x2 is added to a general linear model in order to account for potential effects of two variables x1 and x2 acting together, this type of effect is

interaction effect

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What statistical analysis should be used to test the joint effects of two continous factors on one continous response variable?

Read 3 answers by scientists to the question asked by Martin Kocsis on Jul 30, 2019

Question

Asked 30th Jul, 2019

Martin Kocsis

University of Southampton

What statistical analysis should be used to test the joint effects of two continous factors on one continous response variable?

I have two continous explanatory variables. I assume that the interplay (joint effect) of these variables can predict a third, continous response variable.

What statistical test can be used to test whether the two factors and the response have a statistically significant relationship?

The actual project is aiming to find out whether the interplay of group size and cognitive abilities of members in a primate society can predict the centralisation of the social network.

Primates Statistical Testing Social Networks Cognitive Joints

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All Answers (3)

31st Jul, 2019 Stefan Schulreich

University of Hamburg

Dear Martin,

Sounds like you are interested in what is commonly called an interaction effect. You can test this in a multiple regression where you input the two continuous explanatory variables and their interaction as predictors and the response variable as dependent variable.

To do this, you need to create the interaction term:

1. demean/center both continous explanatory variables (i.e. compute the mean for each variable and substract the mean from the individual values of each variable).

2. compute the interaction term by simply multiplying the demeaned variables (Xdemeaned x Ydemeaned).

3. Then use the demeaned variables and the interaction term as predictors in a multiple regression as stated in the beginning.

If the interaction effect gets significant, you can run further analyses to understand how the interaction looks like and how it can be interpreted.

This can be done via a so-called simple-slopes analysis - Here is a very useful tutorial on that issue (done in SPSS, but same logic in other packages):

https://www.youtube.com/watch?v=ighASZf3eyA

Best, Stefan Cite 1 Recommendation 1st Aug, 2019 Claude Houssemand

University of Luxembourg

Dear Martin,

You have to use regression analysis. Your IV will be the two continous factors and its interaction and your DV your continous response variable. You can use SPSS or Psych R Package.

Best Cite 1st Aug, 2019 Basim Mahmood University of Mosul

Regression analysis can be involved in such investigations. Then, further deep analysis can be involved just to approve your analysis.

Good luck Cite 1 Recommendation

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Term

regression is used to:

Definition

find the best fitting straight line that relates 2 dependent samples in populations

Term

correlation is used to :

Definition

describe the strength of the linear relationship

Term

a correlation coefficient of +/- 1 indicates:

Definition

a perfect correlation

Term

involes the linear relationship btwn one one dependent variable and multiple dependant variables

Definition

multiple regression

Term

used often in epidemiology studies:

Definition

multiple regression

Term

formula for Z score:

Definition

score-mean/SD: Z score of +1 = 1SD above the mean

Term

which test? two independent grps w subjects randomly assigned to groups

Definition

T test

Term

3 assumptions in the T test:1. scores represent normal distribution

Definition

2. sbj randomly selected/assgnd grps

3. variences of the 2 grps are equal

Term

numerator of the T test represents:

Definition

difference btwn grp means

Term

denominator of the T test represents:

Definition

diff btwn grp variances

Term

formula for the degrees of freedom:

Definition

df= total # of df - # of grps

Term

one vs two tail tests: which is less likely to commit a Type II error?

Definition

less likely to commit a type II error using a one tailed test

Term

useful test for when the experimental design is one group that receives before/after tx:

Definition

T test for paired data

Term

Z scores are appropriate for alrge samples but the _____ is more commonly used for small samples (n<30)

Definition

t-distribution

Term

max # of grps you can compare w a T test:

Definition

2

Term

a stat method used to test for differences among three or more tx means:

Definition

ANOVA

Term

2 assumptions of NOVA

Definition

normally distributed data

no sig diff btwn grp variances

Term

instead of a T-test the ANOVA has an:

Definition

F test

Term

F ratio formula:

Definition

F = btwn grp variance/within grp variance

Term

ANOVA used to investigate the effects of ea of several independent variables and the joint effect of these variables acting together:

Definition

factorial ANOVA

Term

the difference btwn the tx variables are called:

Definition

main effects

Term

the ______ effect is due to the joint action of the tx variables:

Definition

interaction effect

Term

multiple comparison test conducted after the primary analysis has rejected the null hypothesis:

Definition

Post-hoc comparisons

Term

multiple comparison test: comparisons of hypotheses specified before the analysis commenced; appropriate even when F test is not significant:

Definition

planned comparisons

Term

4 ex of multiple comparison tests:1. honestly significant difference

Definition 2. newman-keuls

3. multiple range test

4. scheffe's method Term

analysis used when levels of an independent variable are ordered along a continuum.

Definition

trend analysis

Term

test most used for frequency or count data; ex: (# of men,# of deaths, # women w/wo dz)

Definition

Chi square

Term

basic premise of Chi sq: number of sample observations in each category of ea variable:

Definition

observed frequencies

Term

basic premise of CHi sq: # of sample observations in ea category if the null hypothesis is true:

Definition

expected frequencies

Term

4 types of chi sq test:1. goodness of fit

Definition

2. test of independence

3. test of homogeneity

4. McNemar test Term

proportions of a normal curve: +/- 1SD = what% of scores?

Definition

68.26%

Term

proportions of normal curve: what % is within 2sd of mean?

Definition

95.44%

Term

proportions of normal curve: what % is within 3SD from mean?

Definition

99.73%

Term

a Z score of 1 indicates:

Definition

the score is 1 SD above the mean

Term

what % of 14yo have cholesterol of >240?

mean cholesterol @ 14 = 170+/-35

Definition

240-170/35 = 2SD above mean; 2.325% of 14yo have chol>240

Term

likelihood that any one event will occur, given all possible outcomes:

Definition

probability

Term

SD of a theoretical sampling distribution of means:

Definition

standard error of the mean

Term

null hypotheses also reffered to as:

Definition

statistical hypothesis

Term

concluding that a difference exists when none actually does

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