Hi All,
I am currently trying to format my output tables in HTML of PROC LIFETEST.
I am able to play around with the font, text size and alignment in side the table. But is there any way I can align the tables in the way I want to? I.e. Position them in different location in the HTML.
This is the code I have right now,
/*TITME TO EVENT ANALYSIS: KAPLAN-MEIER ESTIMATE */
proc format;
value sexFmt
1 = "male"
2 = "female";
run;
data os;
format patid 10.;
format sex sexFmt.;
call streaminit(6875687);
do patid = 5213 to 9899;
sex = rand("integer",1,2);
event_fl = rand("integer",1,0);
duration_months = rand("integer",6,120);
output;
end;
run;
%macro product_limit_template;
proc template;
source Stat.Lifetest.ProductLimitEstimates;
define table Stat.Lifetest.ProductLimitEstimates;
notes "Product-Limit Survival";
column GrpNumVar GrpChrVar Timelist GenericTime Censor NumberAtRisk ObservedEvents Survival Failure StdErr Failed Left Freq
GenericIDNumeric GenericIDCharacter;
header h1;
define h1;
text "Product-Limit Survival Estimates";
space = 1;
spill_margin;
first_panel;
end;
parent = Stat.Lifetest.ProductLimitEstimates0;
end;
define table Stat.Lifetest.ProductLimitEstimates0;
notes "Survival and Cumulative Hazard";
dynamic TimeNDec TimelistNDec NumWidth NumDec;
column GrpNumVar GrpChrVar Timelist GenericTime Censor NumberAtRisk ObservedEvents Survival Failure StdErr CumHaz StdErrCumHaz
Failed Left Freq Weight GenericIDNumeric GenericIDCharacter;
header h1 h2 h3;
define h1;
text "Survival Function and Cumulative Hazard Rate";
space = 1;
spill_margin;
first_panel;
just=c;
end;
define h2;
text "Product-Limit";
start = Survival;
end = StdErr;
just=c;
end;
define h3;
text "Nelson-Aalen";
start = Cumhaz;
end = StdErrCumhaz;
just=c;
end;
define GrpNumVar;
dynamic GrpVarLab;
translate _val_=._ into "";
label = GrpVarLab;
id;
generic;
end;
define GrpChrVar;
dynamic GrpVarLab;
label = GrpVarLab;
id;
generic;
end;
define Timelist;
define header t;
text "Timelist";
vjust=m;
end;
header = t;
just = c;
format_width = 8;
format_ndec = TimelistNDec;
style = RowHeader;
id;
justify=on;
end;
define GenericTime;
define header t;
text "Duration (&duration_type.)";
vjust=m;
end;
header=t;
format_width = 8;
format_ndec = TimeNDec;
just = c;
space = 0;
style = RowHeader;
id;
generic;
justify=on;
end;
define Censor;
header = " ";
translate
_val_=1 into "*",
_val_=0 into "",
_val_=. into "";
format = 1.0;
id;
end;
define Survival;
define header t;
text "Survival";
vjust=m;
end;
header = t;
format = D8.;
just = c;
justify=on;
end;
define Failure;
define header t;
text "Failure";
vjust=m;
end;
header = t;
format = D8.;
just = c;
justify=on;
end;
define StdErr;
define header t;
text "Survival Standard Error";
vjust=m;
end;
header=t;
format = D8.;
just = c;
justify=on;
end;
define CumHaz;
header = ";Cumulative;Hazard;";
format = D8.;
just = c;
end;
define StdErrCumHaz;
header = ";Cum Haz;Standard;Error";
format = D8.;
just = c;
end;
define Failed;
define header t;
text ";Number;Failed;";
just = c;
end;
header = t;
just = c;
format_width = NumWidth;
format_ndec = NumDec;
justify=on;
end;
define Left;
define header t;
text ";Number;Left;";
just = c;
end;
header = t;
just = c;
format_width = NumWidth;
format_ndec = NumDec;
justify=on;
end;
define NumberAtRisk;
define header t;
text ";Number;at Risk;";
just = c;
vjust= middle;
end;
header = t;
just = c;
format_width = NumWidth;
format_ndec = NumDec;
end;
define ObservedEvents;
define header t;
text ";Observed;Events;";
just = c;
end;
header = t;
just = c;
format_width = NumWidth;
format_ndec = NumDec;
end;
define Freq;
header = "Freq";
format_width = NumWidth;
format_ndec = NumDec;
end;
define Weight;
header = "Weight";
format = D8.;
end;
define GenericIDNumeric;
format = BEST8.;
generic;
data_format_override;
end;
define GenericIDCharacter;
generic;
end;
required_space = 5;
col_space_max = 4;
col_space_min = 1;
end;
define table Base.Template.Table;
end;
run;
%mend product_limit_template;
%macro km_curve(data=, duration_variable=, event_variable=, censor_value=,
duration_type=, timelist=, graph_title=, x_axis_title=, y_axis_title=,
stratification_variable=, condition=1, km_curve_tag=);
%product_limit_template;
ods trace on/ listing;
ods html path="/home/u48457160/OS_HTML/";
ods escapechar="^";
proc odstext;
h "Time To Event Analysis- Kaplan Meier Estimate"/ style={font_size=10 textdecoration=underline};
run;
proc odstext;
h "^S={leftmargin=0.25in} 1. What is Time To Event Analysis?"/ style={font_size=5};
p "Time-to-event analysis is a branch of statistics that studies the amount of time it takes before a particular event occurs, say,
death, or failure of a component. Furthermore, the time to event can be measured in days, weeks, years, etc."/style={font_size=5};
h "^S={leftmargin=0.25in} 2. What is Kaplan Meier Estimate?"/ style={font_size=5};
p "Kaplan-Meier (KM) is non-parametric estimates of survival function that is commonly used to describe
survivorship of a study population and to compare two study populations. It is used to estimate and graph survival probabilities as a function of time"/style={font_size=5};
h "^S={leftmargin=0.25in} 3. Vocabulary"/ style={font_size=5};
p"a. Event: Outcome of interest, for e.g., death, disease occurrence etc ^n
b. Observation time: The time until which a subject’s activities has been captured ^n
c. Censoring: If a subject does not have an event during the observation time, they are censored (nothing is observed or known about that subject after the time of censoring) ^n
d. Right censoring: This is done if a subject leaves the study before the event occurs ^n
e. Left censoring: This is done if the event in interest happens before the start of the study ^n
f. Interval censoring: This is done if they don’t know when exactly the event has occurred but know at what period it has occurred ^n
g. Survival probability: It is also known as the survivor function S(t), is the probability that an individual survives from the time of origin to a specified future time t ^n
h. Median survival: It is the point in time where half the patient population has survived ^n
i. Mean survival: Mean KM estimates are calculated by finding the area under the KM curve
"/ style={font_size=5};
run;
title1 height=10 underlin=1 justify=left "^S={leftmargin=0.25in} Result Generation" ;
title2 height=5 underlin=1 justify=left "^n ^S={leftmargin=0.25in} &graph_title." ;
proc lifetest data=&data. method=km plots=survival(cb=hw test atrisk)
timelist=&timelist.;
%if (&stratification_variable.) ne '' %then
%do;
strata &stratification_variable.;
%end;
time &duration_variable.*&event_variable.(&censor_value.);
where &condition.;
ods output quartiles=quartiles;
ods output means=means;
ods output censoredsummary=censoredsummary;
ods output productlimitestimates=productlimitestimates;
run;
title1;
title2;
ods html close;
ods trace off;
%mend km_curve;
%km_curve(data=os, duration_variable=duration_months,
event_variable=event_fl, censor_value=0, duration_type=months, timelist=12 24
36 48 60, graph_title=OS for All patients, x_axis_title=Time to Event (Month),
y_axis_title=Survival Prob, stratification_variable=, condition=,
km_curve_tag=);
