AllBehavioural_ModelSummary.Rmd

---
title: "All Behavioural Summary and Anova"
output: html_document
---
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# All Anova and summary statistics from behavioural experiments:
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## Plastic Response: Activity

Summary Statistics from each activity experiment: Can open reference scripts for more information:
```{r, echo=FALSE, warning=FALSE, include=FALSE}
setwd('./PlasticResponse_Activity/Scripts/')
source('packages.R')
source('SpiderCues_ActivityAnalysis.R')
source('MantidCues_ActivityAnalysis.R')
source('ComplexCues_ActivityAnalysis.R')
source('Cricket-Spider_ActivityAnalysis.R')
```

Note: hour2 == pi*hour/12

### Spider Cues vs. Control (no cues)
```
  spider_mod_spli_2 <- lmer(activity_counts ~ Treatment*light + sin(hour2) + cos(hour2)  + monitor
                            + (1 + light | individual), data=act_hour)
```
```{r, warning=FALSE}
  summary(spider_mod_spli_2)
  car::Anova(spider_mod_spli_2)
```

### Mantid Cues vs. Control (no cues)
```
  mantid_mod_spli_2 <- lmer(activity_counts ~ Treatment*light + sin(hour2) + cos(hour2)  + monitor
                            + (1 + light | individual), data=Mantid_hour)
```
```{r, warning=FALSE}
  summary(mantid_mod_spli_2)
  car::Anova(mantid_mod_spli_2)
```

### Cricket Cues vs. Spider Cues
```
 Exp2_mod_spli_2 <- lmer(activity_counts ~ sin(hour2) + cos(hour2) + Treatment*light + monitor
                          + (1 + light | individual), data=Exp2_hour)
```
```{r, warning=FALSE}
  summary(Exp2_mod_spli_2)
  car::Anova(Exp2_mod_spli_2)
```

### Spiders fed Flies vs. Crickets vs. Flies vs. Spiders fed Crickets
```
  Exp3_mod_spli_2 <- lmer(activity_counts ~ sin(hour2) + cos(hour2) + Cues*light + monitor
                          + (1 + light | individual), data=Exp3_hour)
```
```{r, warning=FALSE}
  summary(Exp3_mod_spli_2)
  car::Anova(Exp3_mod_spli_2)
```

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## Evolved Response: Activity
```{r, warning=FALSE, include=FALSE, echo=FALSE}
setwd('./EvolvedResponse_Activity/')
source('packages.R')
source('Evolved_Activity_Analysis.R')
```

### Evolved populations activity when no predators are present
```
#hour2 == pi*hour/12

mod_trial_2 <- lmer(Hourly_activity ~ sin(hour2) + cos(hour2) + Treatment + Treatment:Population + light + light:Treatment + start_day + monitor
                    + (1 + light | individual), data=dat.hourly)
```
```{r, warning=FALSE}
summary(mod_trial_2)
car::Anova(mod_trial_2)
```

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## Plastic Response: Courtship
```{r, warning=FALSE, include=FALSE, echo=FALSE}
setwd('./PlasticResponse_Courtship/')
source('packages.R')
source('Plastic_Courtship_script.R')
```

### Courtship Proportion and Counts:

**Proportion of time Courting**
```
courtship_model1 <- lmer(court_prop ~ Treatment + 
                             (1|Date), 
                           data=courtship2 )
```

```{r, warning=FALSE}
  summary(courtship_model1)
  car::Anova(courtship_model1)
```


**Number of Courtship attempts in 15 minutes**
```
courtship_model2 <- lmer(count ~ Treatment  + 
                             (1|Date), 
                           data = courtship2)
```

```{r, warning=FALSE}
summary(courtship_model2)
car::Anova(courtship_model2)
```
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## Plastic Response: Copulation
```{r, warning=FALSE, include=FALSE, echo=FALSE}
setwd('./PlasticResponse_Copulation/')
source('packages.R')
source('Plastic_Copulation_Script.R')
```

**Copulation Latency**
```
copul_lat_mod <- lmer(Cop_latency ~ Treatment + (1|Date), 
                      data = copulation2)
```
```{r, warning=FALSE}
summary(copul_lat_mod)
car::Anova(copul_lat_mod)
```

**Copulation Duration**
```
copul_dur_Mod <- lmer(Cop_Duration ~ Treatment + (1|Date), 
                      data = copulation2)
```
```{r, warning=FALSE}
summary(copul_dur_Mod)
car::Anova(copul_dur_Mod)
```


**Copulation Proportion**

```
copprop_mod <- glmer(copulationSuccess ~ Treatment + (1|Date),
                     data = copulation, family = "binomial")
```

```{r, warning=FALSE}
  summary(copprop_mod)
  car::Anova(copprop_mod)
```

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## Evolved Response: Mating Behaviours

```{r, warning=FALSE, include=FALSE, echo=FALSE}
setwd('./EvolvedResponse_MatingBehaviour/')
source('packages.R')
source('Evolved_Mating_Analysis.R')
```

### Evolved Mating Behaviours: 

Age Bins correspond number of days old the flies were: 1) 1-3, 2) 4-7, 3) 8-11 and 4) 12-15).

**Courtship Latency**
```
  mod_court <- lmer(Rel_Court_lat ~ 1 + Treatment*AgeBin + 
                      (1|Date) + (1|Treatment:Rep), 
                    data = AP_Data)
```
```{r, warning=FALSE}
  summary(mod_court)
  car::Anova(mod_court)
```

**Copulation Latency**
```
  mod_copl_plot <- lmer(Rel_Cop_lat ~ 1+ Treatment*AgeBin + 
                          (1|Date) + (1|Treatment:Rep), 
                        data = AP_Data)
```
```{r, warning=FALSE}
  summary(mod_copl_plot)
  Anova(mod_copl_plot)
```
**Copulation Duration**
```
 mod_copd_plot <- lmer(Rel_Cop_dur ~ 1+ Treatment*AgeBin + 
                          (1|Date) + (1|Treatment:Rep), 
                        data = AP_Data)
```
```{r, warning=FALSE}
  summary(mod_copd_plot)
  Anova(mod_copd_plot)
```
**Copulation Proportion**

Note: Model below is simpified version from origional attempts: some issue with data (presuambly perfect seperation issue) with one age bin*treatment having all 100% sucessful copulations (other attempts == glmer and glmmTMB), but this method was deemed a sufficient method
```
mod_cop_count_glm <- glm(Copulation ~ 1 + Treatment*AgeBin, 
                           family = "binomial", 
                           data = AP_Data)
```

```{r, warning=FALSE}
summary(mod_cop_count_glm)
Anova(mod_cop_count_glm)
```

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## Evolved Response: Mating Behaviours Light vs. Dark

```{r, warning=FALSE, include=FALSE, echo=FALSE}
setwd('./EvolvedResponse_CourtshipLight-Dark/')
source('Light-Dark_Courtship_script.R')
```

The Model:

```
  stuff2 <- lmer(P_court ~ Treatment*Phase + Observer + 
                   (1|Day) + (1|Treatment:Population), 
                 data=court)
  

```

```{r, warning=FALSE}
  summary(stuff2)
  car::Anova(stuff2)
```