Error in taply how to#

Using the data in the table above, a) compute the incidence rate ratio and the incidence rate difference for moderate activity compared to the least active subjects, and b) write an interpretation of your findings. I can do this using the ifelse() function, which has the following format: Suppose my data set has a continuously distributed variable called 'birthwgt', which is each child's weight in grams at birth, but I wish to create a new variable that categorizes children as having Low Birth Weight (lowBW), i.e.

Creating a Dichotomous Variable from a Continuous Variable Using the double equal sign (=) basically means 'only if DrugExp equals 1'. > t.test(Birthwt) # 1-sample t-test to get 95% CI for those unexposed to drugs > t.test(Birthwt) # 1-sample t-test to get 95% CI for those exposed to drugs > sd(Birthwt) sd(Birthwt) # standard deviation for each exposure group > mean(Birthwt) mean(Birthwt) # means for each exposure group Please let me know in the comments, if you have additional questions and/or comments.

Error in taply how to#

Getting descriptive statistics by category can also be achieved as follows: Summary: In this R tutorial you learned how to fix -operator errors. > tapply(Birthwt,DrugExp,t.test) # Gives 95% confidence interval for exposed and unexposed in one outpu t An Alternate Method of Subset Analysis > tapply(Ppregwt,DrugExp,sd) # Gives the standard deviations of pre-pregnancy weight by drug > tapply(Ppregwt,DrugExp,mean) # Gives the means of pre-pregnancy weight by drug exposur e > tapply(Dubow,DrugExp,sd) # Gives the standard deviations of Dubowitz score by drug exposur e If so, the missing values and the line segments joining them are. The response and hence its summary can contain missing values. The basic idea is that if you can execute a computation in X X seconds on a single. Generally, parallel computation is the simultaneous execution of different pieces of a larger computation across multiple computing processors or cores. If x.factor is an ordered factor and the levels are numeric, these numeric values are used for the x axis. Many computations in R can be made faster by the use of parallel computation. > tapply(Dubow,DrugExp,mean) # Gives means of Dubowitz score by drug exposure By default the levels of x.factor are plotted on the x axis in their given order, with extra space left at the right for the legend (if specified). My goal is to sort the data set by DrugExp and then compute the mean and standard deviation of Dubow Scores and Pre-pregnancy weights for each category of DrugExp. To understand clearly lets imagine you have height of 1000. Basically, tapply () applies a function or operation on subset of the vector broken down by a given factor variable. įor example, suppose I have a data set with continuous variables Dubow (Dubow Score), DrugExp (Drug Exposure) and Ppregwt (Pre-pregnancy weight). Apply a function to each cell of a ragged array, that is to each (non-empty) group of values given by a unique combination of the levels of certain factors. Where is the variable that you want to analyze, is the variable that you want to subset by, and is the function or computation that you want to apply to. The basic structure of the tapply command is: For categorical variables you should use the table() function to get counts of categorical variables and use the prop.table() function to get proportions. Note that tapply() is used for descriptive statistics (e.g., mean, sd, summary) for continuously distributed variables. In effect this enables you to subset the data by one or more classifying factors and then performing some function (e.g., computing the mean and standard deviation of a given variable) by subset. The tapply() function is useful for performing functions (e.g., descriptive statistics) on subsets of a data set. Please tell me about it in the comments, in case you have any further comments or questions.Analyzing Data in Subsets Using R The tapply() command Summary: In this article you have learned how to handle the “Error in apply : dim(X) must have a positive length” in the R programming language.

Warnings & Errors in R (List with Examples).

ggplot2 Error: Aesthetics must be either length 1 or the same as the data.

Error in scan: Line 1 did not have X Elements.

Error in as.Date.numeric(X) : ‘origin’ must be supplied.In the video, I’m explaining the R programming codes of this article:įurthermore, you may want to read some of the other articles of my homepage. Have a look at the following video instruction of my YouTube channel. No matter which alternative you choose, keep in mind that the apply function can not be used for one-dimensional data. Mean(data$x1) # Using mean function instead Mean (data$x1 ) # Using mean function instead # 4