diff --git a/parts/designing-surveys/designing-surveys.pdf b/parts/designing-surveys/designing-surveys.pdf index 5ea1463..081edee 100644 Binary files a/parts/designing-surveys/designing-surveys.pdf and b/parts/designing-surveys/designing-surveys.pdf differ diff --git a/parts/designing-surveys/figs/unnamed-chunk-24-1.png b/parts/designing-surveys/figs/unnamed-chunk-24-1.png index e081615..5ac7143 100644 Binary files a/parts/designing-surveys/figs/unnamed-chunk-24-1.png and b/parts/designing-surveys/figs/unnamed-chunk-24-1.png differ diff --git a/parts/designing-surveys/figs/unnamed-chunk-26-1.png b/parts/designing-surveys/figs/unnamed-chunk-26-1.png index d6151d6..e3749e6 100644 Binary files a/parts/designing-surveys/figs/unnamed-chunk-26-1.png and b/parts/designing-surveys/figs/unnamed-chunk-26-1.png differ diff --git a/parts/designing-surveys/index.html b/parts/designing-surveys/index.html index b6573f4..34f8fc3 100644 --- a/parts/designing-surveys/index.html +++ b/parts/designing-surveys/index.html @@ -284,12 +284,12 @@ ``` #> profileID respID qID altID obsID price type freshness -#> 1 38 1 1 1 1 2.0 Honeycrisp Average -#> 2 39 1 1 2 1 2.5 Honeycrisp Average -#> 3 20 1 1 3 1 3.5 Honeycrisp Poor -#> 4 3 1 2 1 2 2.0 Fuji Poor -#> 5 60 1 2 2 2 2.5 Honeycrisp Excellent -#> 6 13 1 2 3 2 3.5 Gala Poor +#> 1 49 1 1 1 1 4.0 Fuji Excellent +#> 2 16 1 1 2 1 1.5 Honeycrisp Poor +#> 3 18 1 1 3 1 2.5 Honeycrisp Poor +#> 4 4 1 2 1 2 2.5 Fuji Poor +#> 5 55 1 2 2 2 3.5 Gala Excellent +#> 6 2 1 2 3 2 1.5 Fuji Poor ``` --- @@ -316,12 +316,12 @@ ``` #> profileID respID qID altID obsID price type_Fuji type_Gala type_Honeycrisp freshness_Poor freshness_Average freshness_Excellent no_choice -#> 1 7 1 1 1 1 4.0 1 0 0 1 0 0 0 -#> 2 46 1 1 2 1 2.5 1 0 0 0 0 1 0 -#> 3 23 1 1 3 1 1.5 1 0 0 0 1 0 0 +#> 1 15 1 1 1 1 1.0 0 0 1 1 0 0 0 +#> 2 27 1 1 2 1 3.5 1 0 0 0 1 0 0 +#> 3 10 1 1 3 1 2.0 0 1 0 1 0 0 0 #> 4 0 1 1 4 1 0.0 0 0 0 0 0 0 1 -#> 5 19 1 2 1 2 3.0 0 0 1 1 0 0 0 -#> 6 34 1 2 2 2 3.5 0 1 0 0 1 0 0 +#> 5 15 1 2 1 2 1.0 0 0 1 1 0 0 0 +#> 6 36 1 2 2 2 1.0 0 0 1 0 1 0 0 ``` --- @@ -350,12 +350,12 @@ ``` #> profileID respID qID altID obsID price type freshness -#> 1 47 1 1 1 1 3.0 Fuji Excellent -#> 2 56 1 1 2 1 4.0 Gala Excellent -#> 3 40 1 1 3 1 3.0 Honeycrisp Average -#> 4 45 1 2 1 2 2.0 Fuji Excellent -#> 5 51 1 2 2 2 1.5 Gala Excellent -#> 6 38 1 2 3 2 2.0 Honeycrisp Average +#> 1 44 1 1 1 1 1.5 Fuji Excellent +#> 2 33 1 1 2 1 3.0 Gala Average +#> 3 37 1 1 3 1 1.5 Honeycrisp Average +#> 4 26 1 2 1 2 3.0 Fuji Average +#> 5 31 1 2 2 2 2.0 Gala Average +#> 6 59 1 2 3 2 2.0 Honeycrisp Excellent ``` --- @@ -401,12 +401,12 @@ ``` #> respID qID altID obsID price type freshness -#> 1 1 1 1 1 3.0 Fuji Excellent -#> 2 1 1 2 1 4.0 Gala Excellent -#> 3 1 1 3 1 3.0 Honeycrisp Average -#> 4 1 2 1 2 2.0 Fuji Excellent -#> 5 1 2 2 2 1.5 Gala Excellent -#> 6 1 2 3 2 2.0 Honeycrisp Average +#> 1 1 1 1 1 1.5 Fuji Excellent +#> 2 1 1 2 1 3.0 Gala Average +#> 3 1 1 3 1 1.5 Honeycrisp Average +#> 4 1 2 1 2 3.0 Fuji Average +#> 5 1 2 2 2 2.0 Gala Average +#> 6 1 2 3 2 2.0 Honeycrisp Excellent ``` --- @@ -529,12 +529,12 @@ ``` #> profileID respID qID altID obsID price type freshness choice -#> 1 47 1 1 1 1 3.0 Fuji Excellent 0 -#> 2 56 1 1 2 1 4.0 Gala Excellent 1 -#> 3 40 1 1 3 1 3.0 Honeycrisp Average 0 -#> 4 45 1 2 1 2 2.0 Fuji Excellent 0 -#> 5 51 1 2 2 2 1.5 Gala Excellent 0 -#> 6 38 1 2 3 2 2.0 Honeycrisp Average 1 +#> 1 44 1 1 1 1 1.5 Fuji Excellent 0 +#> 2 33 1 1 2 1 3.0 Gala Average 0 +#> 3 37 1 1 3 1 1.5 Honeycrisp Average 1 +#> 4 26 1 2 1 2 3.0 Fuji Average 0 +#> 5 31 1 2 2 2 2.0 Gala Average 1 +#> 6 59 1 2 3 2 2.0 Honeycrisp Excellent 0 ``` --- @@ -685,13 +685,13 @@ ``` ``` -#> sampleSize coef est se -#> 1 30 price -0.1289689 0.09703613 -#> 2 30 typeGala 0.3097395 0.19622827 -#> 3 30 typeHoneycrisp 0.4039833 0.19185208 -#> 4 30 freshnessAverage -0.4936206 0.22915332 -#> 5 30 freshnessExcellent -0.2773703 0.21284363 -#> 6 60 price -0.0811527 0.06713569 +#> sampleSize coef est se +#> 1 30 price -0.323720273 0.09703566 +#> 2 30 typeGala -0.006998948 0.19692109 +#> 3 30 typeHoneycrisp 0.310095155 0.18477278 +#> 4 30 freshnessAverage 0.176627903 0.23789479 +#> 5 30 freshnessExcellent -0.189772841 0.24507782 +#> 6 60 price -0.210818382 0.06596601 ``` ] @@ -705,12 +705,12 @@ ``` #> sampleSize coef est se -#> 45 270 freshnessExcellent -0.31731638 0.07674039 -#> 46 300 price -0.08985462 0.02913155 -#> 47 300 typeGala 0.15681599 0.05935676 -#> 48 300 typeHoneycrisp 0.19697765 0.05883549 -#> 49 300 freshnessAverage -0.05403604 0.06891741 -#> 50 300 freshnessExcellent -0.31296763 0.07264400 +#> 45 270 freshnessExcellent -0.21393084 0.07636678 +#> 46 300 price -0.11318500 0.02926127 +#> 47 300 typeGala 0.13458492 0.05885936 +#> 48 300 typeHoneycrisp 0.15370569 0.05876901 +#> 49 300 freshnessAverage 0.08786836 0.07127721 +#> 50 300 freshnessExcellent -0.17724236 0.07268666 ``` ] @@ -787,9 +787,9 @@ # Your turn -- Download the practice zip file for this section. -- Open the `designing-surveys.Rproj` file to open RStudio. -- In RStudio, open the `practice.R` file. +- Be sure to have downloaded and unzipped the [practice code](https://jhelvy.github.io/2023-qux-conf-conjoint/practice/2023-qux-conf-conjoint.zip). +- Open the `2023-qux-conf-conjoint.Rproj` file to open RStudio. +- In RStudio, open the `designing-surveys.R` file. - Experiment with different design options, then examine the power: - What if you modify the quesitons per respondent? - What if you use a labeled design?