similar to: Comparing a 4-point and 5-point Likert scale

Dear colleagues, in the help archive there was a previous person who encountered a problem with the "recode" command in the car library. I'm not sure if that was solved, there was no posting to that effect, but I'm having the same problem. I'm trying to recode a numeric variable with values from 0-100 into a binary variable with values (0,1). The following command:

Dear colleagues, I want to calculate the value of x2 based on the value of x1. x1 is a factor with three separate levels. I want to make sure that missing values remain as NA in X2, but non-missing values take on a value of either 0 or 1 dependending on the value in x1. This is the code I'm working with...Can any one help? I've seen some other requests on a topic like this, but not

Hi all, I have a series of cateogiral variables that look just like this: welfare=sample(c("less", "same", "more"), 1000, replace=TRUE) education=sample(c("less", "same", "more"), 1000, replace=TRUE) defence=sample(c("less", "same", "more"), 1000, replace=TRUE) egp=sample(c("salariat",

Dear colleagues, particularly academic ones, So I'm creating a Microsoft Word template for myself so that every time I teach a new course, I don't have to enter in the dates manually for each class session. I'd like to use an R script that can generate an irregular series of dates starting from one date (semester begin) to another (semester end) using an irregular interval in

Hi everyone, I'm stuck on my dissertation which is due next week. I'm a business major student and my project is a comparative research on corporate social responsibility (CSR) between Chinese and German firms. According to my literature review, it's quite obvious that German firms have much better CSR initiatives and strategies than the Chinese ones and I wanted to test whether it was

I'm working with the following code below to generate a how do I set the h,c, and l values such that the significant, positive residuals appear different on a grayscale printer from significant grayscale residuals. The challenge as I see it is that one can only distinguish the positive and negative residuals with the hue/. Varying the chroma and the luminance only affect the

Dear colleagues, I have extracted the dates of several news stories from a newspaper data base to chart coverage trends of an issue over time. They are in a data frame that looks just like one generated by the reproducible code below. I can already generate a histogram of the dates with various intervals (months, quarters, weeks years) using hist.Date. However, there are two other

Hi, I have just found this forum, and it looks like a great place to get some help (I hope) For my dissertation, which is due way too soon, I am doing a survey, comparing attitudes of 2 independent groups, with 5 scale likert questions. Basically I want to show if they have similar or different attitudes. I am testing 4 hypotheses, and have in total about 20 questions. I have to say my

Dear colleagues, I would like to run a cluster analysis on a number of variables. They are Likert Scale (0 to 10), but they also have a "Don't know' option at the end of the scale. Apparently, with the 'Don't Know' option in place, they cannot be considered to be linear or ordinal. How can these variables be analysed using R? One option would be to use poLC and treat

Hi! I am using R to process some community survey data. Several item responses are recorded via a 7-point Likert-Scale. As I have coded the responses, 1 represents high agreement, and 7 high disagreement. This of course impacts the coefficients in a linear regression (of example agreement to self-perception measures on housing satisfaction). For some purposes, in order to make the coefficients

Hello all, I'm new user with R and just completed a five day course on the program. Somehow, a few basic questions remain unanswered. I'm working on a Mac Os X system and have my laptop connected to a large, flat- screen monitor. I can't make any of the Quartz windows fill the monitor's screen; I'd like to make them full screen to identify points in a dense

R- Help Forum Working with the "likert" package and I can't figure out why my "bar" graphs are backwards (see attached). The percentages are place correctly but the bars are backwards. #Sample code # libraries library(likert) # create data band <- c("Band 3","Band 3","Band 3","Band 3","Band 3","Band

I'm creating a stacked bar chart using the likert command in the HH package. My data are in a data frame, with two numeric variables and a categorical variable, I can't get likert to use the column containing the categorical variable as a my y axis label. Here is a quick example: library(HH) #my data are:

Dear R members Could someone tell me how to simulate Likert-type data using the rnorm function. Let's say, 200*15 random numbers in a variable that goes from 1 to 4 in steps of 1 (i.e., 1, 2, 3, 4) belonging to a normal distribution? random.data <— matrix(rnorm(200 * 15), nrow = 200, ncol = 15) random.data The result cannot be reached. could one help me revise the syntax?

R- Help Forum Working with the "likert" package and find that my "bar" graphs are backwards (see attached) > summary(results) Item low neutral high mean sd 4 Q4 5 15 80 2.75 0.5501196 5 Q5 20 40 40 2.20 0.7677719 1 Q1 65 30 5 1.40 0.5982430 3 Q3 5 90 5 2.00 0.3244428 2 Q2 90 10 0 1.10 0.3077935

Hello, Before I start to construct something inferior myself I would like to know if such a plot function is already out there. I have count data of a small survey with a few questions which use a scale from "Strongly disagree" to "Strongly agree" and similar things. What I would like to have for a slide is a plot which shows for each question a line over this scale and the

Hello all, Is there a way to take the row names from my data.frame and have them imported to the regression results? At the moment, I my original data frame looks like this: / Riding name / Turnout / Margin / Expenditures 1 / Abbotsford 2 / . 3 / . 4 / .Willow I know how to set the row names for the original data frame to be the Riding name, but when I run the regression, the residuals,

Dear colleagues, the code below generated the two effects plots that I have attached. I hope they are not stripped. The original two models are as follows: green_shift_mod=glm(green_shift ~ educ+party_id+educ:party_id, family=binomial, data=x) carbon_tax_mod=glm(carbon_tax ~ educ+party_id+educ:party_id, family=binomial, data=x) Then, I try to plot the effects of party_id by education for

Hello all, I'm having difficulty getting one particular variable into R from SPSS v. 16.0 for mac. R version is 2.10.1. I saved the relevant variables from SPSS into a .csv file and then read them into R. All the variables worked fine, except for one (enviro_spending). In the SPSS file it is correctly coded as a nominal variable and there is nothing that I can tell that

Dear list, I have the following how-to-do it in R, questions. Suppose I have ten independent variables, and one dependent variable. I want to find the Pearson correlation of all the IVs with the DV, but not the correlation between the IVs. What I know so far, about R, that I have to type the cor () function ten times, each time requesting for a correlation between one IV and the DV. I was