Turnout Analysis
combined bjp and
inc
## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

2014 and 2019 turnout
and vote share of BJP and INC
## `geom_smooth()` using formula = 'y ~ x'

Turnout and vote
share scatter of 2009 and 2014
## `geom_smooth()` using formula = 'y ~ x'

Turnout and voteshare
scatter of 2009 and 2019
## `geom_smooth()` using formula = 'y ~ x'

Scatter plot 2009 and
2014 vote share
## $x
## [1] "2009 vote share seatwise"
##
## $y
## [1] "2014 vote share seatwise"
##
## $title
## [1] "Scatter Plot 2009 and 2014 voteshare"
##
## attr(,"class")
## [1] "labels"
## `geom_smooth()` using formula = 'y ~ x'

INC Turnout Change and
Winning Probability
2019
and 2014
## Install package "strengejacke" from GitHub (`devtools::install_github("strengejacke/strengejacke")`) to load all sj-packages at once!
## Rows: 91669 Columns: 45
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (19): State_Name, Candidate, Sex, Party, Candidate_Type, Constituency_Na...
## dbl (20): Assembly_No, Constituency_No, Year, month, Poll_No, DelimID, Posit...
## lgl (6): last_poll, Same_Constituency, Same_Party, Turncoat, Incumbent, Rec...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
##
## Call:
## glm(formula = Category ~ vs_difference_1914, family = "binomial",
## data = main)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.22037 0.14629 -15.177 <2e-16 ***
## vs_difference_1914 -0.04837 0.03716 -1.302 0.193
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 342.82 on 542 degrees of freedom
## Residual deviance: 341.13 on 541 degrees of freedom
## AIC: 345.13
##
## Number of Fisher Scoring iterations: 5
## Data were 'prettified'. Consider using `terms="vs_difference_1914
## [all]"` to get smooth plots.

2009 and 2014
## Rows: 91669 Columns: 45
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (19): State_Name, Candidate, Sex, Party, Candidate_Type, Constituency_Na...
## dbl (20): Assembly_No, Constituency_No, Year, month, Poll_No, DelimID, Posit...
## lgl (6): last_poll, Same_Constituency, Same_Party, Turncoat, Incumbent, Rec...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
##
## Call:
## glm(formula = Category ~ vs_difference_0914, family = "binomial",
## data = main_1)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.84217 0.21269 -8.661 < 2e-16 ***
## vs_difference_0914 -0.09039 0.02733 -3.307 0.000943 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 305.47 on 542 degrees of freedom
## Residual deviance: 293.85 on 541 degrees of freedom
## AIC: 297.85
##
## Number of Fisher Scoring iterations: 5
## Data were 'prettified'. Consider using `terms="vs_difference_0914
## [all]"` to get smooth plots.

2009 and 2019
##
## Call:
## glm(formula = Category ~ vs_difference_0919, family = "binomial",
## data = maiin_2)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.69364 0.17402 -9.733 < 2e-16 ***
## vs_difference_0919 -0.08321 0.01923 -4.327 1.51e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 342.82 on 542 degrees of freedom
## Residual deviance: 323.03 on 541 degrees of freedom
## AIC: 327.03
##
## Number of Fisher Scoring iterations: 5
## Data were 'prettified'. Consider using `terms="vs_difference_0919
## [all]"` to get smooth plots.
