Outliers - females who did not lay eggs
egg_count~day+I(day^2)*mate_type + (1|indv) + (1|trial)
Fecundity rate of females mated to one scrambler or one fighters does not differ
## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## day 16957.4 16957.4 1 614.95 21.3873 4.577e-06 ***
## I(day^2) 1881.6 1881.6 1 615.08 2.3732 0.1239
## mate_type 294.8 294.8 1 88.79 0.3719 0.5435
## I(day^2):mate_type 140.1 140.1 1 536.69 0.1767 0.6744
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## $emtrends
## mate_type day^2.trend SE df lower.CL upper.CL
## F -0.0314 0.00486 587 -0.0409 -0.0218
## S -0.0297 0.00474 596 -0.0391 -0.0204
##
## Degrees-of-freedom method: kenward-roger
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## F - S -0.00163 0.00394 529 -0.415 0.6786
##
## Degrees-of-freedom method: kenward-roger
Kruskal Test: day~mate_type
The time of first egg lay does not differ for females mated with a scrambler or a fighter
Things to note: non parametric test as points were not normally distrubuted. Also looking at each trial as canโt use trial as random effect in nonparametric test
Trial 1:
##
## Kruskal-Wallis rank sum test
##
## data: day by mate_type
## Kruskal-Wallis chi-squared = 0.925, df = 1, p-value = 0.3362
Trial 2:
##
## Kruskal-Wallis rank sum test
##
## data: day by mate_type
## Kruskal-Wallis chi-squared = 0.058511, df = 1, p-value = 0.8089
log(egg_count)~mate_type + day [covariate]
The amount of eggs laid on the first day does not differ between females mated to a scrambler or a fighter
Things to note: had to do separate models by trials as due to error for only have 2 trials
Trial 1:
## Analysis of Variance Table
##
## Response: log(egg_count)
## Df Sum Sq Mean Sq F value Pr(>F)
## mate_type 1 0.0163 0.0163 0.0377 0.847082
## day 1 3.3136 3.3136 7.6500 0.008806 **
## Residuals 37 16.0267 0.4332
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## $emmeans
## mate_type emmean SE df lower.CL upper.CL
## F 2.79 0.147 37 2.50 3.09
## S 2.81 0.147 37 2.51 3.11
##
## Results are given on the log (not the response) scale.
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## F - S -0.0143 0.209 37 -0.068 0.9458
##
## Results are given on the log (not the response) scale.
Trial 2:
## Analysis of Variance Table
##
## Response: log(egg_count)
## Df Sum Sq Mean Sq F value Pr(>F)
## mate_type 1 0.1607 0.16067 0.4441 0.5108
## day 1 0.1562 0.15615 0.4316 0.5168
## Residuals 27 9.7685 0.36179
## $emmeans
## mate_type emmean SE df lower.CL upper.CL
## F 2.69 0.147 27 2.39 2.99
## S 2.87 0.169 27 2.52 3.21
##
## Results are given on the log (not the response) scale.
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## F - S -0.178 0.226 27 -0.785 0.4394
##
## Results are given on the log (not the response) scale.
day~mate_type + egg_count [covariate]
Time of peak fecundity does not differ between females mated to a scrambler or a fighter
Note: two trials due to singularity error with lmer. Log is used for trial 2 only
Trial 1:
## Analysis of Variance Table
##
## Response: day
## Df Sum Sq Mean Sq F value Pr(>F)
## mate_type 1 46.22 46.225 3.8041 0.05873 .
## egg_count 1 2.14 2.145 0.1765 0.67681
## Residuals 37 449.61 12.151
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## $emmeans
## mate_type emmean SE df lower.CL upper.CL
## F 8.22 0.781 37 6.64 9.8
## S 10.33 0.781 37 8.75 11.9
##
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## F - S -2.11 1.11 37 -1.913 0.0635
Trial 2:
## Analysis of Variance Table
##
## Response: log(day)
## Df Sum Sq Mean Sq F value Pr(>F)
## mate_type 1 0.9944 0.99440 2.2162 0.1482
## egg_count 1 0.4959 0.49592 1.1052 0.3024
## Residuals 27 12.1149 0.44870
## $emmeans
## mate_type emmean SE df lower.CL upper.CL
## F 2.01 0.166 27 1.67 2.35
## S 1.73 0.191 27 1.34 2.12
##
## Results are given on the log (not the response) scale.
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## F - S 0.283 0.259 27 1.091 0.2848
##
## Results are given on the log (not the response) scale.
Peak Fecundity does not differ for females mated with a scrambler or a fighter
egg_count~mate_type+day [covariate]
Trial 1:
## Analysis of Variance Table
##
## Response: egg_count
## Df Sum Sq Mean Sq F value Pr(>F)
## mate_type 1 255 255.02 0.2163 0.6446
## day 1 208 208.09 0.1765 0.6768
## Residuals 37 43618 1178.86
## $emmeans
## mate_type emmean SE df lower.CL upper.CL
## F 88.3 7.87 37 72.3 104
## S 91.9 7.87 37 75.9 108
##
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## F - S -3.59 11.4 37 -0.315 0.7545
Trial 2:
## Analysis of Variance Table
##
## Response: log(egg_count)
## Df Sum Sq Mean Sq F value Pr(>F)
## mate_type 1 0.9294 0.92941 2.8785 0.1013
## day 1 0.1987 0.19867 0.6153 0.4396
## Residuals 27 8.7179 0.32289
## $emmeans
## mate_type emmean SE df lower.CL upper.CL
## F 4.28 0.138 27 4.00 4.56
## S 3.93 0.158 27 3.61 4.25
##
## Results are given on the log (not the response) scale.
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## F - S 0.352 0.209 27 1.682 0.1040
##
## Results are given on the log (not the response) scale.
day~mate_type + egg_count [covariate]
Last day of fecundity does not differ for females mated to a fighter or a scrambler
Notes: As above divided by both trials, and trial 2 is logged
Trial 1:
## Analysis of Variance Table
##
## Response: day
## Df Sum Sq Mean Sq F value Pr(>F)
## mate_type 1 81.23 81.225 1.5393 0.22254
## egg_count 1 194.11 194.110 3.6785 0.06286 .
## Residuals 37 1952.44 52.769
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## $emmeans
## mate_type emmean SE df lower.CL upper.CL
## F 16.8 1.64 37 13.5 20.1
## S 18.8 1.64 37 15.5 22.2
##
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## F - S -2.04 2.34 37 -0.874 0.3879
Trial 2:
## Analysis of Variance Table
##
## Response: log(day)
## Df Sum Sq Mean Sq F value Pr(>F)
## mate_type 1 0.3869 0.3869 0.7733 0.38695
## egg_count 1 3.5114 3.5114 7.0182 0.01332 *
## Residuals 27 13.5088 0.5003
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## $emmeans
## mate_type emmean SE df lower.CL upper.CL
## F 2.75 0.173 27 2.39 3.10
## S 2.36 0.199 27 1.96 2.77
##
## Results are given on the log (not the response) scale.
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## F - S 0.384 0.267 27 1.437 0.1622
##
## Results are given on the log (not the response) scale.
Fecundity on the last day does not differ between females mated to a scrambler or a fighter
Note: Divided by trials
Trial 1:
## Analysis of Variance Table
##
## Response: egg_count
## Df Sum Sq Mean Sq F value Pr(>F)
## mate_type 1 616.2 616.22 1.3733 0.24874
## day 1 1650.7 1650.67 3.6785 0.06286 .
## Residuals 37 16603.1 448.73
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## $emmeans
## mate_type emmean SE df lower.CL upper.CL
## F 26.0 4.78 37 16.3 35.6
## S 20.6 4.78 37 10.9 30.3
##
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## F - S 5.35 6.82 37 0.784 0.4380
Trial 2:
## Analysis of Variance Table
##
## Response: egg_count
## Df Sum Sq Mean Sq F value Pr(>F)
## mate_type 1 568.2 568.25 1.5799 0.21954
## day 1 1619.5 1619.51 4.5028 0.04316 *
## Residuals 27 9710.9 359.66
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## $emmeans
## mate_type emmean SE df lower.CL upper.CL
## F 21.0 4.61 27 11.52 30.4
## S 13.9 5.28 27 3.03 24.7
##
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## F - S 7.12 7.03 27 1.013 0.3202
Total fecundity does not differ for females mated to a scrambler or a fighter
Trial 1:
## Analysis of Variance Table
##
## Response: total
## Df Sum Sq Mean Sq F value Pr(>F)
## mate_type 1 25654 25654 1.0024 0.3231
## Residuals 38 972487 25592
## $emmeans
## mate_type emmean SE df lower.CL upper.CL
## F 298 35.8 38 225 370
## S 348 35.8 38 276 421
##
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## F - S -50.6 50.6 38 -1.001 0.3231
Trial 2:
## Analysis of Variance Table
##
## Response: total
## Df Sum Sq Mean Sq F value Pr(>F)
## mate_type 1 68533 68533 3.4103 0.07578 .
## Residuals 27 542593 20096
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## $emmeans
## mate_type emmean SE df lower.CL upper.CL
## F 255 35.4 27 182.0 327
## S 157 39.3 27 76.3 238
##
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df t.ratio p.value
## F - S 97.8 52.9 27 1.847 0.0758
Survival is not impacted by the morph the females mate with but is impacted by egg laying
coxph(Surv(day)~mate_type, data=survival.single)
## Call:
## coxph(formula = Surv(day) ~ mate_type + egg_count, data = survival.single)
##
## coef exp(coef) se(coef) z p
## mate_typeS -0.18567 0.83055 0.24383 -0.761 0.446
## egg_count 0.05670 1.05834 0.01175 4.827 1.39e-06
##
## Likelihood ratio test=17.16 on 2 df, p=0.0001878
## n= 70, number of events= 70