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edit approved Feb 21, 2014 at 12:53
Nick Stauner
edit approved Feb 21, 2014 at 12:53
Nick Stauner
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I have a problem with interpreting 2-way and 3-way interactioninteractions in lmer. My DV is height which is a continuous variable. All IVs are categorical variables. The first factor is animal, either rat or lion. The second factor is sex, either male or female. The third factor is color: red, white, or yellow. I get confused with interpreting the output:

According to Vasishth et alet al. (2007), the significance of fixed effects can be lookedjudged from the absolute t value; if it is higher than 2, then that factor is significant. In interpreting this output, I choose only factors which are significant. Could you pleasePlease check if my interpretations are correct: 1) coloryellow = The height of subjects are lower when they like yellow, and are higher if they like white. 2) rat:colorred = The effect of rat preference enhances the preference of red and these two promotes height of subjects. 3) rat:sexmale:coloryellow = The effect of rat preference, being male enhance the preference of yellow and subjects who like rat and yellow and are male have higher height.

  1. coloryellow = The height of subjects are lower when they like yellow, and are higher if they like white.
  2. rat:colorred = The effect of rat preference enhances the preference of red, and these two promote height of subjects.
  3. rat:sexmale:coloryellow = The effect of rat preference, being male, enhances the preference of yellow, and subjects who like rat and yellow and are male have higher height.

From these interpretations, I would like to ask: if I would like to know the effect of lion:sexfemale:colorredlion:sexfemale:colorred, and rat:sexmale:colorredrat:sexmale:colorred compared to rat:sexfemale:coloorredrat:sexfemale:coloorred, do I have to run the new statistics?

Pete

I have problem with interpreting 2-way and 3-way interaction in lmer. My DV is height which is continuous variable. All IVs are categorical variables. The first factor is animal, either rat or lion. The second factor is sex, either male or female. The third factor is color: red, white, yellow. I get confused with interpreting the output:

According to Vasishth et al (2007), the significance of fixed effects can be looked from the absolute t value; if it is higher than 2, then that factor is significant. In interpreting this output, I choose only factors which are significant. Could you please check if my interpretations are correct: 1) coloryellow = The height of subjects are lower when they like yellow, and are higher if they like white. 2) rat:colorred = The effect of rat preference enhances the preference of red and these two promotes height of subjects. 3) rat:sexmale:coloryellow = The effect of rat preference, being male enhance the preference of yellow and subjects who like rat and yellow and are male have higher height.

From these interpretations, I would like to ask if I would like to know the effect of lion:sexfemale:colorred, and rat:sexmale:colorred compared to rat:sexfemale:coloorred, do I have to run the new statistics?

Pete

I have a problem with interpreting 2-way and 3-way interactions in lmer. My DV is height which is a continuous variable. All IVs are categorical variables. The first factor is animal, either rat or lion. The second factor is sex, either male or female. The third factor is color: red, white, or yellow. I get confused with interpreting the output:

According to Vasishth et al. (2007), the significance of fixed effects can be judged from the absolute t value; if it is higher than 2, then that factor is significant. In interpreting this output, I choose only factors which are significant. Please check if my interpretations are correct:

  1. coloryellow = The height of subjects are lower when they like yellow, and are higher if they like white.
  2. rat:colorred = The effect of rat preference enhances the preference of red, and these two promote height of subjects.
  3. rat:sexmale:coloryellow = The effect of rat preference, being male, enhances the preference of yellow, and subjects who like rat and yellow and are male have higher height.

From these interpretations, I would like to ask: if I would like to know the effect of lion:sexfemale:colorred, and rat:sexmale:colorred compared to rat:sexfemale:coloorred, do I have to run new statistics?

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How to interpret 2-way and 3-way interaction in lmer?

I have problem with interpreting 2-way and 3-way interaction in lmer. My DV is height which is continuous variable. All IVs are categorical variables. The first factor is animal, either rat or lion. The second factor is sex, either male or female. The third factor is color: red, white, yellow. I get confused with interpreting the output:

Fixed effects:
                                  Estimate Std. Error t value
(Intercept)                       164.6888     7.8180  21.065
rat                               -14.1342     8.2889  -1.705
sexmale                           -16.0883    10.0071  -1.608
colorred                            0.5776     6.2473   0.092
coloryellow                        -14.4048     6.1025  -2.360
rat:sexmale                         15.3645    11.8567   1.296
rat:colorred                        12.5258     4.4028   2.845
rat:coloryellow                     10.3136     4.3196   2.388
sexmale:colorred                     2.0272     5.2773   0.384
sexmale:coloryellow                  5.7643     5.1669   1.116
rat:sexmale:colorred                -5.5144     6.2838  -0.878
rat:sexmale:coloryellow              0.9735     6.1690   2.158

According to Vasishth et al (2007), the significance of fixed effects can be looked from the absolute t value; if it is higher than 2, then that factor is significant. In interpreting this output, I choose only factors which are significant. Could you please check if my interpretations are correct: 1) coloryellow = The height of subjects are lower when they like yellow, and are higher if they like white. 2) rat:colorred = The effect of rat preference enhances the preference of red and these two promotes height of subjects. 3) rat:sexmale:coloryellow = The effect of rat preference, being male enhance the preference of yellow and subjects who like rat and yellow and are male have higher height.

From these interpretations, I would like to ask if I would like to know the effect of lion:sexfemale:colorred, and rat:sexmale:colorred compared to rat:sexfemale:coloorred, do I have to run the new statistics?

Pete