survey

How to categorize and tabularize free-form answers to a question in a survey?

由 生来就可爱ヽ(ⅴ＜●) 提交于 2019-12-08 00:33:00
问题 I want to analyze answers to a web survey (Git User's Survey 2008 if one is interested). Some of the questions were free-form questions, like "How did you hear about Git?". With more than 3,000 replies analyzing those replies entirely by hand is out of the question (especially that there is quite a bit of free-form questions in this survey). How can I group those replies (probably based on the key words used in response) into categories at least semi-automatically (i.e. program can ask for

Subsetting Survey Design Objects Dynamically in R

由 拥有回忆 提交于 2019-12-07 20:32:07
问题 I am trying to figure out how to subset a survey design objects dynamically. I have structured my loop to send in character strings, and don't know how to remove the quotes so R reads it as a call. I would like to loop through some like this (although this will obviously break because SUBSET_VARIABLE %in% 4 needs to be a call NOT a string. : design <- svydesign( ~1 , weight = ~wt , data = mtcars ) for( SUBSET_VARIABLE in c("gear","carb") ){ design <- subset( design , SUBSET_VARIABLE %in% 4 )

Combining Survey Items in R/ Recoding NAs

由 一个人想着一个人 提交于 2019-12-07 17:21:39
问题 I have two lists (from a multi-wave survey) that look like this: X1 X2 1 NA NA 2 NA NA How can I easily combine this into a third item, where the third column always takes the non-NA value of column X1 or X2, and codes NA when both values are NA? 回答1: Combining Gavin's use of within and Prasad's use of ifelse gives us a simpler answer. within(df, x3 <- ifelse(is.na(x1), x2, x1)) Multiple ifelse calls are not needed - when both values are NA , you can just take one of the values directly. 回答2:

Ionic 2 Multiple Checkboxes with FormBuilder

由 风流意气都作罢 提交于 2019-12-07 14:07:07
问题 Survey app checkbox photo I currently faced the issue of building the form on multiple choice questions. At this moment, the form for single choice works well, only left multiple choice questions. The goal I want to have is something like this: { "questions": [ // if multiple choices question { "question_id": 17, "answer_ids": [81,82,83] }, { "question_id": 20, "answer_ids": [101,102,104] } ] } survey.ts this.surveyForm = this.formBuilder.group({ questions: formBuilder.array([]) }) for (var i

best way to store survey data?

由 馋奶兔 提交于 2019-12-06 07:49:58
问题 I am developing a very small survey application, likely 3-4 pages web application. so my question is what is the best way to save survey data? by the way so far I have come up with the following ways. save to database and mark each survey as incomplete. when user submits last form of the survey check completeness of the survey and mark it as complete if it is complete. save to sessions and than save to database when user submits last form of the survey. what do you think about those methods?

Methods in R for large complex survey data sets?

由 强颜欢笑 提交于 2019-12-06 06:16:18
问题 I am not a survey methodologist or demographer, but am an avid fan of Thomas Lumley's R survey package. I've been working with a relatively large complex survey data set, the Healthcare Cost and Utilization Project (HCUP) National Emergency Department Sample (NEDS). As described by the Agency for Healthcare Research and Quality, it is "Discharge data for ED visits from 947 hospitals located in 30 States, approximating a 20-percent stratified sample of U.S. hospital-based EDs" The full dataset

How can I generate marginal effects for a logit model when using survey weights?

由 a 夏天 提交于 2019-12-06 03:49:21
问题 I normally generate logit model marginal effects using the mfx package and the logitmfx function. However, the current survey I am using has weights (which have a large effect on the proportion of the DV in the sample because of oversampling in some populations) and logitmfx doesn't appear to have any way to include weights. I have fitted the model with svyglm as follows: library(survey) survey.design <- svydesign(ids = combined.survey$id, weights = combined.survey$weight, data = combined

Is it impractical to put an HTML form into an email? [closed]

由 一个人想着一个人 提交于 2019-12-05 01:51:54
I've had several clients ask this, and I've never been able to get or give a satisfactory answer. Can you (practically) put a working form into an HTML email? My understanding is that you can, but that there's no guarantee of email clients properly handling it, so that method would only be practical with individual recipients that you'd had a chance to test with, rather than with huge mailing lists of people using diverse email clients. But my understanding comes from a lot of developer friends shrugging at the question and no authority that I've found giving a clear answer either way. What

best way to store survey data?

由 为君一笑 提交于 2019-12-04 11:43:21
I am developing a very small survey application, likely 3-4 pages web application. so my question is what is the best way to save survey data? by the way so far I have come up with the following ways. save to database and mark each survey as incomplete. when user submits last form of the survey check completeness of the survey and mark it as complete if it is complete. save to sessions and than save to database when user submits last form of the survey. what do you think about those methods? I've had quite some headaches with this sort of thing and would advise against using Sessions if at all

How can I generate marginal effects for a logit model when using survey weights?

由 ≡放荡痞女 提交于 2019-12-04 07:07:38
I normally generate logit model marginal effects using the mfx package and the logitmfx function. However, the current survey I am using has weights (which have a large effect on the proportion of the DV in the sample because of oversampling in some populations) and logitmfx doesn't appear to have any way to include weights. I have fitted the model with svyglm as follows: library(survey) survey.design <- svydesign(ids = combined.survey$id, weights = combined.survey$weight, data = combined.survey) vote.pred.1 <- svyglm(formula = turnout ~ gender + age.group + education + income, design = survey
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